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cpse Centre for Process Systems EngineeringAnnual Report 2014–2015

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Introduction 4

Highlights 2014–2015 5

Industrial Consortium 9

CPSE Research Programme 11

Competence Areas 13

Product Process and Design 14

Operations and control 16

Modelling and Model Solution Tools 20

Computational Optimisation and Machine Learning 22

Application Domains 26

Chemical Manufacturing Systems 27

Molecular Systems Engineering 30

Biological Systems Engineering 32

Energy Systems Engineering 34

Environmental Systems Engineering 36

Supply Chains of the Future 40

Academic Profiles 41

CPSE Academics and Staff Directory 84

CPSE Research Project List 86

PhD Graduates 2014–2015 96

Contents 2014–2015 CPSE Annual Report

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“It has been a great pleasure to see CPSE grow in size and breadth, while continuing to excel in both fundamentals and applications.”

Welcome to the 2014–2015 CPSE Annual ReportProfessor Nilay ShahCPSE Director

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Understanding the Performance of Complex Systems

We have a sense that the words we use to describe the complexity of the modern world provide only a superficial understanding of the underlying mechanisms of the processes upon which we depend.In 1989, Professor Roger Sargent gathered together a group of engineers, mathematicians and molecular scientists and established the Centre for Process Systems Engineering to define and quantify the components that make up complex industrial chemical processes in order to optimize performance.

Since then our field of work has expanded to encompass many other critical industrial and biological systems and has led to the development of algorithms and computer simulations that describe individual processes, from the molecular to macroscopic scale, that combine to define, for example: a bacterial cell’s ability to produce a synthetic oil; the design of an optimized urban energy system and the economics of a commodity supply chain. Statistical routines have been developed to model the performance of complex systems even in the absence of full descriptions of all the contributory components.

CPSE History

International Research Leader in Process Systems Engineering

The Centre for Process Systems Engineering (CPSE) is a multi-institutional research centre. It was inaugurated in August 1989 by Professor Roger W.H. Sargent and involves Imperial College London and University College London.

A report by a panel of external, international experts to theEPSRC research council described CPSE as being “one of the major centres of excellence in its area of expertise in the world and is seen as the benchmark against which other world centres are judged”.

Innovative and dynamic in its approach to research and development, CPSE’s accomplishments include the Queens Prize for Higher Education, presented in 2003 for research excellence and technology transfer.

Three spin-out companies have been established. One of these, Process Systems Enterprise Limited (PSE), received the Royal Academy of Engineering’s MacRobert Award in 2007; this is the UK’s highest award for innovation in engineering.

The Centre continues to broaden the scope of its activities over all size scales enabling all areas of process systems to be addressed. This enables CPSE to be responsive to the evolving needs of industry and society. Centre for Process Systems EngineeringImperial College LondonRoderic Hill BuildingSouth Kensington CampusLondon, SW7 2AZEmail: cpse@imperial.ac.ukhttp://www.imperial.ac.uk/process-systems-engineering/

Introduction 2014–2015 CPSE Annual Report

The Centre for Process Systems Engineering draws upon the world-leading skills of Imperial College London and University College London

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Centre for Process Systems Engineering (CPSE)

The CPSE continues to deliver a unique multi-disciplinary approach to Process Systems Engineering. The number of academic staff has expanded to over 30 to meet the growing demand for research and education in this critically important subject.

The group has an annual research income portfolio of £30M. Since it was founded in 1989, CPSE has used its expertise in Process and Product Design, Operations and Control and Modelling and Model Solution tools to investigate a wide range of technically and commercially important issues. The scope of CPSE continues to evolve and adjust to changes in technology and commercial needs with work underway, for example, in new areas such as ‘Environmental Systems’ and ‘Computational Optimisation and Machine Learning.’

New Academics

During 2014 and 2015, the number of academics grew following the affiliation of eight new members from both Imperial College London and University College London: Dr Marc Deisenroth, Lecturer in Statistical Machine Learning, Department of Computing; Dr Adam Hawkes, Senior Lecturer in Energy Systems; Dr Federico Galvanin, Lecturer, Department of Chemical Engineering; Dr Gonzalo Guillén-Gosálbez, Reader in Process Systems Engineering, Dr Alexandros Kiparissides (former CPSE PhD student) Lecturer in the Department of Biochemical Engineering; Dr Niall Mac Dowell (former CPSE PhD student) Lecturer in Energy and Environmental Technology and Policy; Dr Ruth Misener, Royal Academy of Engineering Fellow, Lecturer, Department of Computing; Dr Wolfram Wiesemann (former CPSE PhD student) Assistant Professor, Business School.

Departing Academics Former CPSE Director, Professor Stratos Pistikopoulosleft Imperial College to join Texas A&M University. Professor Pistikopoulos was a great supporter of CPSE, having led the Centre for seven years (2002-2009). Professor Pistikopoulos will continue to be a member of CPSE as Visiting Professor.

Research Excellence

The CPSE’s acclaimed leadership in Process Systems Engineering is highlighted by the number of papers in prestigious publications. In the last two years, there have been over 300 publications. Many papers by CPSE researchers have been recognised for their originality, significance and influence.

A paper co-authored by Professor George Jackson on the Statistical Associating Fluid Theory (SAFT), was selected as one of the ‘All Time Greats’ in the history of Industry & Engineering Chemistry Research (I&ECR). The paper, ‘New Reference Equation of State for Associating Liquids’ by Walter G. Chapman, Keith E. Gubbins, George Jackson, and Maciej Radosz, I&ECR 29, 1709, (1990), describes an approach which permits scientists to make precise predictions about the behaviour of a broad range of liquids including solutions of polymers and surfactants.

A paper by the Molecular Systems Engineering Group was listed as “one of the most accessed in 2014” from The Journal of Chemical Physics. The paper is entitled ‘Accurate statistical associating fluid theory for chain molecules formed from Mie segments’, by Thomas Lafitte, Anastasia Apostolakou, Carlos Avendaño, Amparo Galindo, Claire S. Adjiman, Erich A. Müller and George Jackson, J. Chem. Phys. 139, 154504 (2013)

Another paper from the Molecular Systems Engineering Group was selected as “one of the 12 most notable papers”, out of 425 papers, published in the proceedings of the 12th International Symposium on Process Systems Engineering held in Copenhagen. The paper is entitled ‘Deterministic global optimization and transition states’, by Claire Adjiman and Dimitrios Nerantzis, Elsevier, Amsterdam, 851–856 (2015).

Further endorsement was received for a book, ‘Distillation: 1. Fundamentals and Principles, 2. Operations and Applications, 3. Equipment and Processes’ which won the 2015 PROSE Chemistry & Physics Award. Professor Andrzej Górak, Editor of Chemical Engineering and Processing: Process Intensification and Professor Eva Sørensen, Editor in Chief of Chemical Engineering Research and Design as well as their co-authors (Hartmut Schoenmakers and Zarko Olujic) received the award at the Association of American Publishers’ (AAP) Professional and Scholarly Publishing (PSP) Annual Conference in Washington, DC. Awarded for the best in professional and scholarly publishing, the book addresses important current research on industrial distillation, process design, operation and control aspects, and conceptual design.

Highlights 2014–2015 CPSE Annual Report

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Academic Distinctions and Awards

The Centre’s reputation is further enhanced by the prestigious national and international awards received by CPSE academics. CPSE academics are international leaders in their fields and have multi-disciplinary backgrounds, including: chemical engineering, mathematics, physics and chemistry. Their expertise has been recognised by numerous awards.

IChemE honoured CPSE’s founding father Professor Roger Sargent, considered the “Pioneer of Process Systems Engineering.”, by creating a new medal in his name, called the Sargent Medal for research in computer-aided product and process engineering. The IChemE established the medal in recognition of the work of members of the chemical engineering academic community who have contributed significantly to the advancement of the profession and society. Professor Costas Pantelides was the recipient of the Sargent Medal for 2015.

Two CPSE academics were amongst the 2014 IChemE winners. Professor George Jackson won the Guggenheim Medal for research excellence in thermodynamics and/or complex fluids. Dr Niall Mac Dowell won the Nicklin Medal for exceptional contribution to the process sciences by an author who has graduated within the last ten years.

Professor Nilay Shah and Professor Claire Adjiman were elected Fellows of the Royal Academy of Engineering. The Academy’s Fellowship represents “the nation’s best engineering researchers, innovators, entrepreneurs, business and industry leaders.” Election to the Academy is by invitation only.

Professor Eva Sørensen won the highly prestigious Inspiration Award for Women which supports Breakthrough Breast Cancer. Professor Sørensen featured on a list of luminaries which included J.K. Rowling and Maya Angelou. Professor Sørensen was nominated for the Inspirational Teacher Award but was instead awarded an Inspiration Award for her outstanding contributions to education at University College London and further afield.

Dr Benoît Chachuat and Dr Ruth Misener each won an AIChE Computing & Systems Technology Division (CAST) Award. Dr Benoît Chachuat received the CAST Outstanding Young

Researcher Award. The award is given to an individual under the age of 40 for outstanding contributions to the chemical engineering computing and systems technology literature. Dr Chachuat is the first to have won this award outside of the USA. Dr Ruth Misener won the David Smith, Jr. Graduation Publication Award. The award is given to “an individual for outstanding published work in chemical engineering computing and systems technology.” The publication consists of work done whilst pursuing graduate studies. Dr Misener received the award for her manuscript: R. Misener, C. A. Floudas, GloMIQO: Global Mixed-Integer Quadratic Optimizer, Journal of Global Optimization, 57, 3-30 (2013).

Professor Geoffrey Maitland was inaugurated the 74th President of IChemE. Immediately after becoming president, Professor Maitland launched the ChemEng365 blog. The daily blog catalogues 365 chemical engineering successes and achievements.

Dr Wolfram Wiesemann become a Fellow of the new KPMG Centre for Advanced Data Analytics. The centre is funded by KPMG with £10m directly (£20m total). The Centre will focus on five core areas of research: Capital, Growth, People, Operations and Resilience. The focus will be on ground-breaking analytics techniques and algorithms that will put the UK at the forefront of data science.

Professor Costas Pantelides was awarded the Imperial College President’s Medal for Excellence in Innovation and Entrepreneurship.

Highlights 2014–2015 CPSE Annual Report

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Student Distinctions and Awards

Once again, all of our graduates who were applying for jobs were successful. Below are examples of some of the awards they have won.

Thapanar Suwanmajo (supervisor Dr J Krishnan) and Pongsathorn Dechatiwongse (supervisor Professor Geoffrey Maitland) won the 2014 Anglo-Thai Education Awards in the Engineering/Technology category. The Award for Excellence is given to Thai postgraduate students studying in the UK who have exceptional academic achievements.

Ioscani Jiménez Del Val (supervisor Dr Cleo Kontoravdi) won the Dudley Newitt Prize for Computational/Theoretical Excellence.

Susie Sou (supervisor Dr Cleo Kontoravdi) won the best poster prize at the UK Meeting of the European Society for Animal Cell Technology in Nottingham.

María Fuentes Gari (supervisor Professor Sakis Mantalaris) won second prize at the 2nd Young Entrepreneur Award Competition (YEA). YEA is an international business plan competition organized by the Fourth Valley Concierge Corporation and Asia Innovators’ Initiative. President, Nobuyuki Idei, Former CEO of Sony Corporation presented the award.

Aiman Alam-Nazki (supervisor Dr J Krishnan) won an EPSRC Prize Fellowship. The Prize Fellowship is a scheme intended to help universities attract and retain the very best newly qualified PhD graduates, who have been supported by the EPSRC. Aiman Alam-Nazki also won the Dudley-Newitt Prize for Theoretical/Computational Excellence, an award given annually to the best thesis in the Chemical Engineering Department at Imperial in this category.

CPSE students dominated the awards at the Qatar Energy R&D Award for two years running. 2014, Tareq Al-Ansari (co-supervisor Professor Nilay Shah) and in 2015, Ibrahim Daher (co-supervised by Professor Geoff Maitland and Dr John Crawshaw) won the Qatar Energy R&D Award.

Images: (top left) Professor Nilay Shah (CPSE Director), Tony Tan Keng Yam (President of the Republic of Singapore) and Professor Alice Gast (Imperial College President) (left) Naveed Tariq and his Team win BBC’s Eggheads(above) Philanthropic Support from Alumni – Izzati Mohd Noor, the first to receive the Marit Mohn PhD Scholar

Tareq and Ibrahim were recognised as rising stars in the Gulf State of Qatar winning the award for their outstanding PhD research which could have a major impact on industry in Qatar.

Post Doctorate Distinctions and Awards

Yun-Bo Zhao (supervisor Dr J Krishnan) was selected in the 1000Plan programme for young talent. The initiative aims to recruit, and provide financial support for outstanding scientists and leading experts who will work in China and play a leading role in the development of high-tech industries or new fields of study in the nation’s major innovation projects, key programmes of study or laboratories, central enterprises or state-owned financial institutions, or high-tech development zones or industrial parks.

High Profile Events

President of the Republic of Singapore’s VisitIn October 2014, the President of the Republic of Singapore, Tony Tan Keng Yam was hosted and given a tour of the Carbon Capture Pilot Plant by Professor Nilay Shah (CPSE Director) and Professor Alice Gast (Imperial President).

17th British-French-German ConferenceA number of CPSE academics, students and researchers were part of the team that organised the 17th British-French-German Conference on Optimisation. The conference was 17th of the series of French-German meetings which started in Oberwolfach, Germany in 1980. Since 1998, the conference has been organised under the participation of a third European country. This time it was jointly organized with Britain and took place at Imperial College London. The conference consisted of invited plenary talks, parallel invited and contributed sessions. The conference was organised by Imperial College London, the Department of Computing, the Centre for Process Systems Engineering and the Imperial College Business School.

Enhancing Education

The CPSE continued to expand and develop education in Process Systems Engineering.

New Courses

Optimisation CoursesThe CPSE identified the need for technical training in optimisation and to address this created two new courses. In April 2015, the first course took place with participants from CPSE Industrial Company Members and PhD students.

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• The Introduction to Optimisation Course provides an introduction to concepts in problem formulation and solution

methods for linear, nonlinear and mixed-integer problems, focusing on local optimisation methods, with a brief introduction to global optimisation.

• The Advanced Optimisation Course builds on the introductory course and focuses on concepts in global optimisation, bilevel optimisation, dynamic optimisation, optimisation under uncertainty.

Detailed information on the courses is available on the CPSE website.

Part-time MSc in Process AutomationThe modular part-time MSc in Process Automation, Instrumentation and Control was launched in December 2014. The aim of the programme is to broaden and deepen the expertise and experience of personnel employed in process automation, either in the design and development of control and related systems, in their application, or in their operation and management. A highlight of the year has been accreditation of the programme by IChemE, IET and the Institution of Measurement and Control.

New Institutions

CPSE has been instrumental in the creation of two new institutes. Sustainable Gas Institute (SGI)Professor Nigel Brandon (Director) and Dr Adam Hawkes (Deputy Director) launched the Sustainable Gas Institute (SGI) in May 2014. The Institute is a unique academic-industry partnership and a ground-breaking collaboration between the United Kingdom and Brazil. Their role is to lead research and define innovative technologies that enable natural gas to play a key role in a low-carbon world. The institute is a multi-disciplinary organisation operating on a ‘hub and spoke’ model, with their international research hub at Imperial College London and spokes in development at leading research universities around the world with a particular focus on Brazil. They manage, lead and deliver world-class research with global partners across the spectrum of science, engineering, economics and business.

Institute for Molecular Science and Engineering (IMSE)Professor Claire Adjiman (Co-Director) and Professor Nicholas Harrison (Co-Director) established the Institute for Molecular Science and Engineering (IMSE) in August 2015. IMSE is one of Imperial College London’s Global Institutes, drawing on the strength of it’s four faculties to address some of the grand challenges facing the world today. The Institute’s activities are focused on tackling problems where molecular innovation plays an important role. The Institute brings together researchers from a diverse range of specialisms to network, communicate and collaborate. The institute also connects these researchers with a wide spectrum of stakeholders including industrialists, interested individuals, government representatives, and researchers from other academic institutions, to enhance discovery and innovation within the molecular field.

Lectures and Seminars

LecturesAnnual Professor Roger W. H. Sargent LectureOn the first Thursday in December, CPSE annually celebrates its founding Academic Father Professor Roger Sargent through the Professor Roger W. H. Sargent Lecture. This tribute to Professor Sargent celebrates his legacy in the field of Process Systems Engineering. Recent eminent speakers who delivered the lectures are:

2015 Professor Venkat Venkatasubramanian, Columbia University. “Process Systems Engineering at Crossroads: Challenges and Opportunities in the Era of Watson.”

2014 Professor Stratos Pistikopoulos FREng, CPSE, Imperial College London. “Multi-Parametric Programming & Control 25 years later: what is next?”

Seminars CPSE has been running a successful Seminar Series for many years and each year we invite distinguished national and international experts to the Centre. For over six years Dr J Krishnan has been organising the CPSE Seminar Series. From 2015, Dr Ruth Misener and Dr Panos Parpas have taken on the tradition of hand picking speakers from around the world. CPSE Industrial Consortium members are all welcome to attend these seminars.

2014 CPSE Seminar SeriesProfessor Arthur D. Lander, University of California, Irvine, CAProfessor Nick Sahinidis, Carnegie Mellon UniversityProfessor L. N. Trefethen, University of Oxford

2014 Special Seminars Professor Julio Banga, CSIC, Spain Professor Ambros Gleixner, Zuse Institute BerlinProfessor Ignacio E. Grossmann, Carnegie Mellon University Professor Jay H. Lee, Daejeon, KoreaMr Hernan Leovey, Humboldt UniversityDr Mark Peters, UNISAProfessor B. Erik Ydstie, Carnegie Mellon University

2015 CPSE Seminar SeriesProfessor Ana Barbosa-Póvoa, Técnico Lisboa, Portugal Professor Robert Bixby, Gurobi, USAProfessor Leo Liberti, École Polytechnique ParisTech, France Professor Alexander Mitsos, RWTH Aachen Professor Kim Chuan Toh, National University of Singapore Professor Philippe Toint, Université de Namur, Belgium

This is my last Annual Report publication as the Director of CPSE. I will be stepping down and passing on the reins to Claire Adjiman on 1st August 2016 and moving to the post of Head of Department of Chemical Engineering at Imperial College London. It has been a great pleasure to see CPSE grow in size and breadth, while continuing to excel in both fundamentals and applications. I leave it in the capable hands of Claire, however, I will remain part of CPSE. Professor Nilay Shah, CPSE Director.

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“Members of the Industrial Consortium can scope out opportunities for optimising their interaction with CPSE through company-specific workshops and one-to-one interaction with leading academics across a broad range of disciplines.”

CPSE Industrial Consortium Graham Elkes

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Companies have increasing pressures to stay ahead of their competitors. They need to be innovative, continuously launch new products and improve existing products and processes. In today’s global market companies are faced with additional pressures to make their operations more energy efficient, safe and environmentally benign. Science and Engineering play a vital role in underpinning the success of the majority of today’s commercial businesses. the CPSE Industrial Consortium provides “a one-stop-shop” for companies seeking solutions to improve their products and operations. Member companies are invited to become involved in the specification, development, validation and final commercial implementation of algorithms, software tools and methodologies derived from leading-edge generic research performed in the Centre. Our members also have opportunities to guide our research and development resources through joint programmes and MSc projects. They are able to access and review technology in one or half-day workshops designed in conjunction with individual members, as well as, participating in additional technology focus briefings for specific sectors. We also hold an annual meeting hosted by CPSE at Imperial College. This includes the annual Roger Sargent lecture, short lectures by research students, guest lectures by consortium members, research updates by academic staff and opportunities for informal social and technical meetings.

Our members join the CPSE Industrial Consortium to gain• Privileged access to world-class academics from two top

universities. CPSE academics between them have over 500 years of research experience. They come from many disciplinary areas including: chemical engineering, mathematics, physics and chemistry and are leaders in their fields.

• Access to well-trained PhD students and Post Doctoral researchers. The Consortium provides opportunities for members to interact with the Centre at many levels. Members are able to evaluate and recruit high calibre PhD students and Researchers from around the world.

• The opportunity to exploit and develop research and resources. Members have the opportunity to guide research development and resources towards their own business needs and have access to all the non-confidential reports of work carried out by the Centre.

• Partnerships: Membership opens the opportunity for the creation of partnerships. Some consortium members have recognized the need to develop in-depth and long-term research relationships with CPSE and have opted to establish Partnerships.

• Links to other Imperial College and UCL Departments. Imperial College and UCL have many other world-class departments which

can be accessed through consortium membership. Members will be directed to key academics in both universities.

• Access to worldwide networking with major companies. The consortium provides a neutral platform for intercompany networking and benchmarking with some of the largest multinational companies.

• Staff training: the consortium provides an opportunity for company employees to attend courses on optimisation.

• A member of academic staff (“friend”) as a liaison point for your company

We offer:• At least one active collaborative research project• Interns for flexible internship projects• An annual, company-specific workshops to scope out

opportunities• A warm welcome to company staff to secondments in CPSE• The CPSE Newsletter• A one-stop-shop for systems engineering technology and

solutions to problems• Access to facilities and expert assistance for cutting edge

software evaluation• The provision of opportunities for inter-company networking and

benchmarking• A credible, world-class partner for joint proposal development

and joint projects• Opportunities for member companies to interact with the Centre

at a range of levels• Access to an exclusive members-only website

Industrial Consortium Company Members

Company Academic FriendABB Corporate Research Professor Nina Thornhill AkzoNobel Professor George Jackson BP Professor Nilay ShahExxonMobil Dr Ruth MisenerPetrobras Professor David BoglePraxair Dr Benoît ChachuatPSE Professor Costas Pantelides Proctor and Gamble Professor Erich Müller Shell Research & Technology Professor Geoffrey MaitlandSyngenta Professor Claire Adjiman

CPSE Industrial Consortium

The Centre started the Industrial Consortium when it was inaugurated in 1989 to address challenges facing industry

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“Research carried out over the last few years has shown that the modelling techniques developed for the process industries by CPSE can deepen our understanding of a wide range of complex systems from the chemical processes within living cells to national energy supply chains.”

CPSE Research ProgrammeProfessor Claire Adjiman

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Application Domains

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Modelling and Model Solution Tools

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Operations and Control

Process and Product Design

Computational Optimisation and Machine Learning

CPSE Research Programme

A new competence area has been created called Computational Optimisation and Machine Learning to focus on developing in a rapidly evolving area.

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“The CPSE offers a unique experience to graduates, including the opportunity to work with internationally renowned academics and some of the biggest industrial companies in the world.”

Competence AreasDr Benoît Chachuat

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CPSE research in Product and Process Design tackles the constraints and objectives imposed by today’s business environment, in particular, in the field of sustainable development.

We take into account the economic, environmental, safety and health aspects and use systematic model-based methodologies for the rational design of processes encompassing a growing range of scales, such as:• Nano-scale models for materials selection• Meso-scale models for design of specific processes • Overall process models for integrated plant design

There are several themes within Product and Process Design, however, the areas that we are concerned with are: Materials design for process synthesis such as development of methodologies property prediction techniques; the design problems with a large number of degrees of freedom (molecular structure, microstructure, formulation variables etc.) Another theme is the design of novel manufacturing processes. Here we are interested in the development of models and techniques for design of state-of-the-art processes, with a particular emphasis on fine chemicals and pharmaceuticals. We also look at the integrated process synthesis and the development of tools for the analysis of interactions between design and operability. Technology transfer is also an interesting theme which still requires more study. In particular, the facilitation of more mature technologies to industrial partners still remains a challenge.

Figure 1: Drinking water is a limited resource

Water Treatment – Predictive modelling of conventional clean water treatmentEva SørensenA major challenge currently facing a sustainable future is the ever increasing demand for clean water of adequate quality and quantity.

Traditionally, the water industry relied on civil engineering to solve its challenges but the expertise in the chemical-engineering field is being increasingly relied upon. Chemical engineers can play a vital role in reducing water losses by transferring knowledge from the process industry to the provision and distribution of potable water. The objective of the work in CPSE focuses on the development of predictive mathematical models based on first principles and the application of optimisation techniques to provide an optimal process flowsheet.

Figure 2: Creating a model representation of water treatment processes and their interactions to mitigate risk

Currently, work within the clean-water industry relies heavily on empirical/hydraulic models. This is due to the clean-water industry being quite traditional in the way it approaches its problems. However, it is slowly realising the importance of maintaining a competitive edge. Our research looks at deriving individual unit models and validating and combining units and considering plant-wide operation. By incorporating the use of mathematical models that can describe the processes, we believe industry can develop its understanding of a unit and be able to find more cost-effective solutions.

To create a model representation of water treatment processes and their interactions to mitigate risk

• Each unit is derived and validated separately and then uses a plug flow reactor (PFR) model to represent the distance the water has to travel between various process units

• The process flowsheet is used to reflect the units operated, chemical additive processes and the physical processes that can be modelled using first principles to deepen the understanding of how each unit operation works.

Competence Area Product Process and Design

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Figure 3: Optimisation of WTW based on superstructures

The advantage of having a dynamic model of a clean water treatment process is invaluable. To demonstrate the applicability of the overall plant model, a sensitivity analysis can be performed by considering the impact of a disturbance propagating through the process for an illustrative case study, where the concentration for source of raw water inlet changes. The case study is implemented in gPROMS. The results produced are reflective of how a system would react to a change like this.

There are various different processing units available for each specific process type. For example, coagulation and flocculation can occur in a CSTR or the chemical coagulant can be injected at one point and allowed to flow through different chambers creating a turbulent flow. There can be multiple units of the same process in parallel as well as for different water sources; some unit configurations work better.

Rational mixture design: optimisation-based approachesClaire S Adjiman and Suela Jonuzaj

The formulation of mixtures offers a potential route to enhanced performance across a wide range of chemical engineering applications, from separation processes to product design. However, mixture design can be very challenging because it requires finding the optimal number, identities and compositions of mixture components and using nonlinear property models, which results in complex nonlinear problems with a large combinatorial space. Thus, a restricted version of the problem is usually posed, where the number of mixture ingredients is fixed in advance, before other design decisions are made. This restricts our ability to identify the optimal mixture.

In view of these challenges, our work focuses on developing a comprehensive and systematic methodology within the Computer-Aided Mixture/blend Design framework by combining mathematical

modelling, optimisation and chemical engineering insights to formulate the general mixture problem. Within this approach, the optimal number of components in a mixture, their identities and compositions are determined simultaneously. A logic-based methodology, Generalised Disjunctive Programming, is used to express the general mixture problem within a mathematical framework and formulate the discrete choices inherent in the problem.

The novel framework proposed has been applied successfully to the design of solvent mixtures for separation processes, including crystallisation and liquid-liquid extraction. Significant benefits can accrue by employing this approach in product design, especially as the number of desirable mixture components increases: the explicit evaluation of every choice of the number of components is avoided, making it possible to consider larger design spaces.

The work has been published in Jonuzaj et al. (2016) and Jonuzaj and Adjiman (2016), and will be presented as a keynote at the 26th European Symposium on Computer Aided Process Engineering (http://escape26.um.si/).

Jonuzaj S., Akula P. T., Kleniati P. M., Adjiman C. S., 2016. The formulation of optimal mixtures with Generalized Disjunctive Programming: A solvent design case study. AIChE Journal. DOI: 10.1002/aic.15122.

Jonuzaj S., Adjiman C. S., 2016. A Convex Hull formulation for the design of optimal mixtures. In: 26th European Symposium on Computer Aided Process Engineering. Available online: http://escape26.conforganizer.net/upload/escape26/abstracts/files/26-efe3-Jonuzaj-and-Adjiman_Escape26.pdf.

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Process Operations uses mathematical models that capture the underlying science of a process and adopts an optimization approach to give improved operation in terms of product quality, energy usage, environmental impact and sustainability. The research within the Centre covers optimization of the operations of existing plants, optimal designs for new plants that take account of dynamic operation at the design stage, management of supply chains and of batch processing.

Process control covers the theory and practice of advanced automation and control applied to a wide variety of processes including reaction, adsorption, granulation and polymerization carried out within a spectrum of manufacturing industries including oil & gas. Competencies feeding into applications include: integration of design; operation and decision making; multi-scale modelling; integrated monitoring of processes; electrical and mechanical equipment; and theoretical advances in robust parametric control. A special feature of the programme is the ability to move new theory rapidly towards practical realisation and thus to help the process control sector take early advantage of new developments.

A selection from the activities in the past year includes:

Multi-parametric NCO-tracking controllers for linear dynamic systems Driven by the need to improve performance and reduce economic costs in industrial processes, on-line optimization and real-time control have been receiving a lot of attention. The strategy employed in classical model predictive control (MPC) is to solve the optimization problem in a receding horizon manner. This is often a rather computationally demanding task that may cause serious delays especially for systems with fast dynamics, leading to suboptimal performance or even infeasibility. In the multi-parametric programming paradigm, the optimization is performed off-line, resulting in a priori explicit mapping of the solutions, effectively control strategies as a function of measurable quantities. Likewise, NCO tracking is a measurement-based optimization approach to enforcing optimality in the presence of uncertainty, via tracking of the necessary conditions for optimality (NCO).

This project is concerned with a methodology for combining multi-parametric programming and NCO tracking into a unified framework for model predictive control, for which we coined the name “multi-parametric NCO-tracking control”. Such a combination is especially promising in that using feedback laws tracking the optimality conditions inside a multi-parametric controller has the potential to dramatically reduce the number of critical regions compared with classical mp-MPC controllers based on time discretization. Moreover, multi-parametric programming provides a means for relaxing the fixed switching structure assumption in NCO-tracking, thereby paving the way towards a theoretical justification for NCO-tracking too. Our initial focus has been on constrained linear dynamic systems, and extensions to the general nonlinear case are now being investigated.

Figure 1: Comparison between the critical regions in a mp-NCO-tracking controller (top plot; 11 regions) and a mp-MPC controller over 50 stages (bottom plot; 1687 regions) for a constrained FCC unit operated in partial combustion mode.

Competence Area Operations and Control

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Robust MPC using set-based methods Classical MPC control is based on a certainty-equivalence principle, whereby the future of the system is optimized as if neither external disturbances nor model mismatch were present. Although these uncertainties are the main reason why feedback is needed in the first place, the main advantage of certainty-equivalence in MPC is that the resulting optimization problems can often be solved efficiently, in real time. Moreover, this approach works well in many practical applications, and it often exhibits a certain robustness due its inherent ability to reject disturbances. However, the constraints may become violated when large disturbances occur, since uncertainty is not taken into account in optimizing the predicted state trajectories. In such cases, robust MPC schemes may be used to mitigate these optimistic predictions.

Our focus in this project is on robust MPC schemes using set-based methods, known collectively under the name tube-based MPC. The predicted trajectory is replaced by a robust forward invariant tube (RFIT) in the state-space, namely a tube that encloses all possible state trajectories under a given feedback control law, which is independent of the uncertainty realization. In contrast to existing methods which parameterize the control law, our approach introduces a min-max differential inequality exploiting the properties on the boundary of RFITs. These min-max differential inequalities provide sufficient conditions for a time-varying convex-set-valued function to be an RFIT, for an inclusive class of input-affine nonlinear control systems. We also derive practical implementations of tube-based MPC based on ellipsoidal calculus, which (i) scale linearly with the length of the prediction horizon, and (ii) do not rely on a particular parameterization of the control law. In principle, this approach can achieve arbitrary precision insofar as the tubes are represented with sufficient accuracy. The construction of robust MPC controllers with such properties is unprecedented for nonlinear input-affine systems.

This work is a collaboration with ShanghaiTech (Dr. Houska) and the University of Freiburg (Prof. Diehl).

Figure 2: Ellipsoidal RFIT for robust MPC control of a constrained spring-mass-damper system, along with three uncertainty realizations (dashed blue lines).

Process Automation Research Programme

Worldwide, there is a huge inventory of currently installed process plants and our research finds ways of helping these to run efficiently and smoothly. This is achieved by optimizing the operation of the process and equipment by detection and diagnosis of the root causes of process inefficiencies. The methods make use of all available information, not only measurements from operating processes but also qualitative and connectivity information from process schematics and drawings, plus reasoning from scientific first principles.

Process plants depend upon mechanical and electrical equipment. We are looking at measurements from the mechanical and electrical sub-systems to understand the whole picture and are also exploring the interactions between a.c. transmission grids and process plants which are large electrical consumers. The work is being undertaken by Imperial researchers, industrial research engineers on secondment and PhD students sharing their time between Imperial and industrial placements with collaborating companies. More information on Process Automation is available at: http://www3.imperial.ac.uk/processautomation

Detection of DisturbancesThe process automation group develops methods for detection and diagnosis of process disturbances. Recently, the work has examined transient disturbances in multi-rate systems. The motivation for these developments is that there is an increasing industrial requirement for the analysis of data sets comprising measurements from industrial processes together with their associated electrical and mechanical equipment. These systems are increasingly affected by transient disturbances, and their measurements are commonly sampled at different rates. Progress with these objectives is illustrated in Figure 3.

The methods are based on nearest-neighbours techniques, meaning that they identify occurrences of similar patterns in the time trends. They build a vector of anomaly indices which are high for the period with the transient disturbance. The general applicability of the above methods is well illustrated by case studies from oil and gas plants and from an experimental compressor rig where process measurements are treated together with electrical measurements from the variable speed drive.

Recently the same methods have been used for automated detection of transient events in an electrical transmission grid as measured by instruments called Phasor Measurement Units. Power system disturbances generally result from the penetration of heavy or light loads, sudden changes in the operation conditions, and faults.

The timescale is much faster than that of events in a process system. Detection of power-system disturbances is a difficult task because of system complexity, diversity of operating conditions and interference from noise. It places high demands on reliable, sensitive and real-time implementation. The successful results show that methods can be adapted across time scales.

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Figure 3: Disturbance detection methods for transient and multirate systems.

The work has received financial support from the Portuguese Foundation for Science and Technology (FCT) under FellowshipSFRH/BD/61384/2009, from the Marie Curie FP7-IAPP project “Using real-time measurements for monitoring and management of power transmission dynamics for the Smart Grid – REALSMART”,Contract No: PIAP-GA-2009-251304, and from EPSRC EP/L014343/1 “Stability and Control of Power Networks with Energy Storage (STABLE-NET)”.

Multi-criterion manufacturability indices for ranking high-concentration monoclonal antibody formulationsThe need for high-concentration formulations for subcutaneous delivery of therapeutic monoclonal antibodies (mAbs) can present manufacturability challenges for the final ultrafiltration/diafiltration (UF/DF) step. Viscosity levels and the propensity to aggregate are key considerations for high-concentration formulations.

This project created a novel framework for deriving a set of manufacturability indices related to viscosity and thermostability to rank high-concentration mAb formulation conditions in terms of their ease of manufacture. This is illustrated by analysing published high-throughput biophysical screening data that explores the influence of different formulation conditions (pH, ions and excipients) on the solution viscosity and product thermostability.

The project used a decision-tree classification method, CART (Classification and Regression Tree) to identify the critical formulation conditions that influence the viscosity and thermostability. The ultimate industrial deliverable from the work was a set of stress maps which show viscosity and thermostability as functions of the formulation conditions and time profiles during UF/DF.

The framework helped to identify the optimal formulation conditions that minimize the potential for both viscosity andaggregation issues during UF/DF.

The work is a sub-project of the EPSRC Centre for Innovative Manufacturing in Emergent Macromolecular Therapies led with UCL. It is sponsored by EPSRC and pharmaceutical companies including GE Healthcare, GlaxoSmithKline, Pfizer and MedImmune.

ReferencesCai, L., Pal, B.C. and Thornhill, N.F., 2016, Multivariate detection of power system disturbances based on fourth order moment and singular value decomposition, submitted to IEEE Transactionson Power Systems.

Cecilio, I., Ottewill, J.R., Fretheim, H., and Thornhill, N.F., 2015, Multivariate detection of transient disturbances for uniandmulti-rate system IEEE Transactions on Control SystemsTechnology s, 23, 1477-1493,

Cecilio, I., Ottewill, J.R., Pretlove, J., and Thornhill, N.F., 2014, Nearest neighbors method for detecting transient disturbancesin process and electromechanical systems, Journal of ProcessControl, 24, 1382-1393.

Operations and Control – Highlighted project

Supercritical gas recycle for surge control of CO2 centrifugal compressorsThe highlighted project concerns computer-based design and analysis of control systems for centrifugal compressors when the operating fluid is supercritical CO2. The work has implemented a non-linear dynamic model including a main forward compression line together with hot and cold recycles. The work is based on a validated model of a CO2 compressor station in collaboration with the industrial partner.

Industrial compressor trains typically use both hot and cold gas recycle for the purposes of surge avoidance. The idea is that the operating fluid is recycled back to the compressor inlet if the flow rate reduces such that the operating point of the compressor approaches the surge line. Hot recycling feeds fluid back to the compressor inlet directly through the recycle valve, while cold recycling also cools the fluid. Ideally recycling would be avoided since recycling of already-compressed fluid represents a waste of energy. On the other hand, the compressor must be protected from surge, and at the same time must fulfil delivery of the operating fluid to the downstream processes or pipeline in the right thermodynamic state. The analysis in this project has provided some insights into the dynamics and control of the two configurations.

The work demonstrated that compared to the hot recycle, the process configuration including a cold gas recycle has better overall stability, but higher power consumption and lower values for the control performance indicators. Moreover it compares subcritical and supercritical compression during surge prevention and highlights the importance of the selection of the gas recycle configuration when full recycle is needed. The key findings are outlined in the table on the right.

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The work was funded by the Marie Curie Marie Curie FP7-ITN project “Energy savings from smart operation of electrical, process and mechanical equipment – ENERGY SMARTOPS”, PITN-GA-2010-264940,and by EPSRC EP/J020788/1 Gas-FACTS: Gas – Future Advanced Capture. Thank you also to ESD Simulation Training for their encouragement, advice and technical support for the project ReferencesBudinis, S., and Thornhill, N.F., 2015, Supercritical gas recycle analysis for surge control of centrifugal compressors, Computer Aided Chemical Engineering (Proceedings of ESCAPE 25), 37, 1583-1588, 2015.

Budinis, S., and Thornhill N.F., 2016, Supercritical gas recycle for surge control of CO2 centrifugal compressors, submitted to Computers & Chemical Engineering (invited paper).

Cold recycle

Advantages: No issues of overheating since the recycled gas is cooled. No loss of machine integrity if the machine runs continuously in recycle mode.

Hot recycle

Advantages: Simple layout and rapid response due to short pipe runs. Less gas is recycled than with cold recycle system. Better pressure control performance.

Recycle of subcritical CO2

Cold recycle circulates 23% more gas than hot recycle and hence equipment sizing will be similar. Designs may be based on considerations outlined above in this table.

Disadvantages: Repeated opening and closing of the recycle valve occurs because the inlet pressure increases when recycled fluid is fed back. This causes interaction between the surge control system and the pressure control system. Higher overall power consumption and lower pressure control performance

Disadvantages: Repeated opening and closing of the recycle valve can occur because recycle of hot gas increases the inlet temperature, which has an impact on the location of the surge region. The machine can overheat due to the high temperature of the recycled gas. Therefore the duration of operation with hot recycle is limited.

Recycle of supercritical CO2

Cold recycle circulates 82% more gas than hot recycle due to the change of state from supercritical to subcritical. Therefore cold recycle may be more effective for supercritical CO2 surge protection.

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Competence Area Modelling and Model Solution Tools

The development of new and improved Modelling and Model Solution tools is a key factor in maintaining the excellence of CPSE’s academic research and has led to many of the software packages in this area that are now the accepted standards in industry.

The models and solution tools in use and under development in CPSE focus on different spatial and temporal scales across a wide range of process systems engineering problems. Four recent examples are described below:

Zacros Zacros is a Kinetic Monte Carlo software package written in Fortran and developed at UCL for simulating molecular phenomena on catalytic surfaces. The tool enables researchers in the areas of Computational Catalysis and Surface Science to perform dynamic modelling of adsorption, desorption, surface diffusion, and reaction processes on heterogeneous catalysts. The rates of these elementary processes are typically computed from ab initio simulations, thereby enabling the prediction of catalytic performance metrics (such as activity and selectivity) from first principles, and the detailed validation of hypothesised kinetic mechanisms against experimental data.

The package employs the Graph-Theoretical KMC methodology coupled with cluster expansion Hamiltonians and Brønsted-Evans-Polanyi relations, which can naturally capture: steric exclusion effects for species that bind in more than one catalytic site; complex reaction patterns involving adsorbates in specific binding configurations and neighbouring patterns; spatial correlations and ordering arising from adsorbate lateral interactions that involve many-body contributions; changes in the activation energies of elementary events, influenced by the energetic interactions of reactants with neighbouring spectator species.

The software was commercialised by UCL Business in Nov-2013, and has a dedicated website (http://zacros.org) with documentation, tutorials, list of publications and links to e-Lucid, the UCL online licensing portal from where users can obtain Zacros from. The code can be obtained free of charge by academics, and since inception it has been distributed more than 70 users in 25 countries worldwide. For more information about Zarcos please contact Michail Stamatakis (m.stamatakis@ucl.ac.uk).

Global Sensitivity Analysis (GSA) GSA is used to identify key parameters whose uncertainty most affects the output. This information can then be used to rank variables, fix unessential variables and decrease problem dimensionality1, 2. Over the last decade GSA has gained acceptance among practitioners in the process of model development, calibration and validation, analysis of problem structure, reliability and robustness analysis, decision-making under uncertainty, quality-assurance, and complexity reduction3. The variance-based method of global sensitivity indices (SI) developed by Sobol’ has become the method of choice among practitioners due to its efficiency and ease of interpretation. However, there is an important class of practical design problems involving inequality constraints imposing structural dependences between model variables in addition to potential correlations between them.

The development of efficient computational approaches for constrained GSA (cGSA) is challenging because the feasible domain of the model variables’ variation may have an arbitrary shape including non-convex or disconnected (as opposed to hyperrectangular spaces considered within conventional GSA).

We have proposed a novel concept of constrained Global Sensitivity Analysis which adds the ability to analyse model output variance in such domains. The advantage of the presented formulations is that no prior knowledge of conditional or marginal distributions is assumed. All the required dependences are derived from the joint p.d.f. and, furthermore, in the presence of constraints it is sufficient to know the joint p.d.f. corresponding to the unconstrained formulation.

Grid cubature and Monte Carlo estimates have been proposed for the evaluation of main and total effect indices. The new approach amounts to greatly expanding the scope of GSA to a wide range of situations of practical importance involving inequality constraints.

For more information about GSA please contact S. Kucherenko and O.V. Klymenko.

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Figure 1

Set-Valued Integration of Uncertain Dynamic Systems Many engineering design and control problems can be formulated, analyzed and solved in a set-based framework. When it comes to designing a control system for instance, the constraints, uncertainties and design specifications are described naturally in terms of sets. In measuring the effect of a disturbance on a system’s response or in bounding the error of an estimation algorithm likewise, sets play a central role. A number of key set-theoretic concepts were proposed in the early 1970s, but their systematic application was not possible until enough computational capability became widely available. Today, many such methods and tools are available for the estimation and control of linear systems, but it is less so for nonlinear systems.

The development of set-valued integration algorithms for uncertain dynamic systems has been an on-going research area in Dr Chachuat’s group for over 10 years. Central to these approaches is the ability to compute tight enclosures of the range of multivariate systems, e.g.,using ellipsoidal calculus or higher-order inclusion techniques based on multivariate polynomials. In recent years, we have developed efficient methods, both continuous-time and discretized approaches, capable of propagating generic set-parameterizations in order to yield tight enclosures on the reachable set of an uncertain ODE or DAE system. Moreover, sufficient conditions that guarantee stability of the bounding system have been identified for the first time.

For more information on set-valued integration please contact Benoît Chachuat.

Simulation of long-term global energy transitionsThe 5th Assessment Report of Working Group 3 of the Intergovernmental Panel on Climate Change was released at the end of 2014, setting out approaches to climate-change mitigation.A number of models were used to support this study, each being global in scope, with long time horizons to capture the dynamics of climate change, and particularly to explore approaches to limiting average surface temperature rise to less than 2ºC.The importance of these models has increased as a result of the Paris Agreement, further pushing the ambition to limit temperature rise to 1.5ºC.

Figure 2: bounds on the reachable set (shaded area) of a two-step anaerobic digestion model with uncertain initial conditions. The coloured lines correspond to different set-parameterizations and expansion orders.

Figure 3: Basic schematic of the MUSE (modular energy system simulation environment). The market clearing algorithm iterates amongst all sectors until they agree on price and quantity for each energy commodity.

The Sustainable Gas Institute is developing a new energy systems simulation environment. Instead of using intertemporal optimisation like many other models, it strives to simulate investment and activity in each sector of the global economy (split into roughly 30 regions) in a way that is appropriate for each sector. The model is bottom-up, including engineering detail and basic economic characteristics for thousands of technologies. It is built on the principles of simplicity and transparency, and the modelling framework will ultimately be made open source. For further information about global energy systems modelling please contact Adam Hawkes.

1 Saltelli A. Tarantolla S., Campolongo F., Ratto M. (2004). Sensitivity analysis in practice, Wiley, New York.

2 Saltelli A., Annoni P., Azzini I., Campolongo F., Ratto M., Tarantola S. (2010) Comput. Phys. Comm. 181 (2): 259–270.

3 Kucherenko S., Feil B., Shah N., Mauntz W. (2011) Reliability Engineering and System Safety, 96:440–449.

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Competence Area Computational Optimisation and Machine Learning

The Computational Optimisation Group has a 30-year track record of research in decision-making under uncertainty, stochastic and robust optimisation. Current interests of the group include representing uncertainty in optimisation models, designing numerical optimisation algorithms and computational software frameworks, and applying these algorithms to energy production, capacity planning, manufacturing and distribution models under uncertainty,

financial engineering and risk management. The Statistical Machine Learning Group focuses on Bayesian methods. Application areas include autonomous systems, robotics, time series analysis, reinforcement learning, and brain-machine interfaces. Several other groups within CPSE also have strands of research in computational optimisation.

Area Academic Expertise

Bayesian Optimisation Deisenroth, Misener Algorithm design, Optimisation for machine learning, Parameterestimation

Optimisation-based Control Bogle, Chachuat, Deisenroth, Dua

Dynamic optimisation, Multiparametric programming, Optimal Control

Implementations & Software Adjiman, Chachuat, Fraga, Kucherenko, Misener

Deterministic global optimisation, Global sensitivity analysis, Set-membership estimation, Mixed-integer nonlinear optimisation, Multi-objective optimisation

Large-Scale Convex Optimisation

Parpas Multiscale optimisation

Machine Learning Deisenroth Gaussian processes, Reinforcement learning, Bayesian inference, Graphical models, Active learning/optimal design

Mixed-Integer Nonlinear Optimisation

Adjiman, Chachuat, Misener alphaBB, Algorithm design, Cutting planes, Deterministic global optimisation, Implementations & software, Multivariable relaxations

Multilevel Optimisation Adjiman, Rustem, Wiesemann Bilevel optimisation, Minimax, Semi-infinite optimisation

Optimisation under uncertainty

Rustem, Wiesemann, Fraga Chance-constrained systems, Risk management, Robust optimisation, Stochastic optimisation

Signal Processing Deisenroth Bayesian state estimation, System identification, Inference and learning in nonlinear dynamical systems

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Highlighted Project Bayesian Optimisation with Dimension Scheduling: Application to Biological Systems

Highlighted Project Authors: Doniyor Ulmasov, Caroline Baroukh (INRA, France), Benoît Chachuat, Marc Peter Deisenroth, Ruth Misener.Bayesian Optimisation (BO) is a data-efficient, global black-box optimisation method optimising an expensive-to-evaluate fitness function; BO uses Gaussian Processes (GPs) to describe a posterior distribution over fitness functions from available experiments. Similar to experimental design, an acquisition function is applied to the GP posterior distribution over fitness functions to suggest the next (optimal) experiment.

Dynamic models of biological processes allow us to test biological hypotheses while running fewer costly, real-world experiments. We consider estimating biological parameters (e.g., reaction rate kinetics) by minimising the squared error between model and experimental data points. Specifically, we propose BO for efficient parameter estimation of a dynamic microalgae metabolism model (Baroukh etal., 2014). The forcing function is based on light exposure and nitrate input; experimental data have been collected for measurable outputs including lipids, carbohydrates, carbon organic biomass, nitrogen organic biomass and chlorophyll. Our method is general and may be applied to any process model.

There are several timescales for collecting microalgae metabolism data: an experiment may take 10 days while each model simulation of Baroukh et al. (2014) runs in a fraction of a second. BO is traditionally applied to functions with expensive evaluation costs, e.g., running a 10 day experiment, but the objective of this paper is testing biological hypotheses; we are specifically interested in running the simulation model many times for parameter estimation.

In biological parameter estimation, BO is challenging because the parameters interact nonlinearly and the broad parameter bounds result in a huge search space. Due to the high problem dimensionality (in this context, 10 parameters), balancing exploration versus exploitation becomes more intricate and traditional Bayesian methods do not scale well. Therefore, we introduce a new Dimension Scheduling Algorithm (DSA) to deal with high dimensional models. The DSA optimises the fitness function only along a limited set of dimensions at each iteration. In each iteration, a random set of dimensions is selected to be optimised. This reduces the necessary computation time, and allows the dimension scheduling method to find good solutions faster than the traditional method. The increased computational speed stems from the reduced number of data points per GP and the reduced input dimensions in the GP; GPs scale linearly in the number of dimensions but cubically in the number data points. Additionally, considering a limited number of dimensions at each node allows us to easily parallelise the algorithm.

Compared to commercial parameter estimation for biological models and a traditional Bayesian Optimisation algorithm, our approach achieves strong performance in significantly fewer experiments and a reduced computation time. We also design and provide a graphical user interface (GUI), which allows untrained users to optimise any model that can be invoked through a command line. The framework removes the barrier of programming language by providing the user with a straight forward user interface to set BO parameters, observe the optimisation as the code runs, and examine the GP after the experiment has been completed.

Highlighted Project References:• C. Baroukh, R. Munoz-Tamayo, J.-P. Steyer, O. Bernard, 2014.

DRUM: A new framework for metabolic modeling under non-balanced growth. application to the carbon metabolism of unicellular microalgae. PLoS ONE 9 (8), e104499.

• D. Ulmasov, C. Baroukh, B. Chachuat, M.P. Deisenroth, R. Misener, 2015. Bayesian Optimization with Dimension Scheduling: Application to Biological Systems. arXiv preprint arXiv:1511.05385.

• Misener R., Floudas C.A. ANTIGONE: Algorithms for coNTinuous / Integer Global Optimization of Nonlinear Equations, Journal of Global Optimization; 59: 503 – 526, 2014.

Deterministic Global Optimization in Nonlinear Optimal Control

Benoît Chachuat, Boris Houska, Nikola Perić. The problem addressed in this project is in the broad field of global optimization of dynamic systems. In a society where competitiveness and sustainability are two major drivers, this problem has attracted a lot of attention by the PSE community over the last two decades. Nevertheless, existing methods fail to provide a certificate of global optimality for systems having more than a handful of time-invariant inputs (controls), let alone systems with time-varying inputs.

Dr Chachuat’s group has contributed a new algorithmic framework, called branch-and-lift, that enables guaranteed global optimization of optimal control problems, without the need for a priori parameterization of the time-varying inputs. Branch-and-lift essentially yields an extension of the branch-and-bound concept to infinite-dimensional Hilbert space. It could be established that the branch-and-lift algorithm terminates finitely for inequality-constrained, input-affine dynamic systems under mild conditions. Preliminary results with case studies indicate that branch-and-lift greatly mitigates the curse of dimensionality and cuts the computational time by several orders of magnitude. These results are particularly significant in that they open, for the first time, the prospect of applying global and robust dynamic optimization technology to industrially relevant problems. On-going work involves developing an efficient implementation of the branch-and-lift algorithm, by building upon the advanced bounding techniques for dynamic systems.

This project is an on-going collaboration with Professor Houska (ShanghaiTech University, China).

Figure 1: Convergence of branch-and-lift for a bioreactor control problem (right plot), and illustration of limited clustering occuring when lifting the search space dimension M (left plot)

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Dynamic optimisation of dynamic systems subject to uncertainty (Carlos Perez-Galvan, David Bogle – CONACyT)

Many process engineering problems have critical bounds (quality, safety or environmental) that must be satisfied at all times. These methods are desirable in applications such as guaranteed

parameter estimation, optimal control, and safe critical applications where critical variables such as safety or environmental performance are an issue. In a dynamic optimisation algorithm guaranteed bounds on the dynamic variables of the models that describe processes are needed in order to solve the problem to global optimality in a rigorous way. Hence, verified bounds are a key step in the optimisation algorithm (Focus on first box of Figure 1). However, the construction of tight bounds is still an issue for practical applications. This project focuses on obtaining bounds that tightly enclose the representation of the reachable set.

Dynamic simulationVerified methods of initial value problems (IVP) for ordinary differential equations (ODE) provide enclosures which are guaranteed to contain all the possible solutions of a problem (possibly subject to an uncertain value). The bounding method used

in this project consists of two stages. The first stage is the validation of existence and uniqueness of a solution in which also a suitable a priori enclosure and a time step are obtained. The second stage involves the computation of a tighter enclosure in which a high order Taylor series is used to refine the solution obtained in the first stage.

Reduction of the overestimationThe major challenge in these methods is the reduction of the overestimation generated in the integration process which is mainly caused by the dependency and wrapping effect problems. This project addresses the reduction of the overestimation and the novel part of the method is the implementation of non-linear interval contractors such as Krawczyk, Newton/ Gauss-Seidel and Forward-Backward.

Figure 1 represents the construction of bounds for an exothermic batch reactor using the interval Taylor series method with different interval contractor implementations, namely, no contractor (NC), Newton and Krawczyk (K) contractors. The grey lines represent the reachable set; they have been constructed using Monte Carlo simulations (2000 samples).

Figure 1. Dynamic optimisation of dynamic system using a sequential approach

Figure 2. Bounds constructed by interval Taylor series method without contractors (NC) and with Newton (N) and Krawczyk (K) contractors.

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Global optimisationThe algorithms with the Newton and Krawczyk contractors have been implemented in a global optimisation algorithm. The algorithm consists of a branch-and-bound tree, the node on which to branch was the one with the least lower bound. At each node, the variable with the greatest diameter (distance between its upper and lower bound) was selected for branching. The first order sensitivity calculations were included in order to discard regions not containing zero in its gradient.

Figure 3 shows a graph of an oil shale pyrolysis example in which the black line represents the optimal profile and the rest of the lines represent suboptimal trajectories. The algorithm which makes use of the interval Taylor series with contractors is able to obtain upper and lower bounds on the global optimum of this problem.

Figure 3. Global optimisation subject to uncertainty of the oil shale pyrolysis process

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“CPSE researchers are taking Process Systems Engineering research into new domains such as nanotechnology, healthcare and sustainability.This is leading to powerful new methods applicable for solving an even wider range of challenges facing chemical engineers in industry.”

Application DomainsProfessor David Bogle, CPSE Deputy Director

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Many of the fundamental tools deveveloped in the four competence areas of Product & Process design, Operations & Control, Modeling and Model Solution Tools, and Optimization & Machine Learning are motivated by the challenges arising from chemical manufacturing systems. This application domain explores the need for new technologies, more effective use of new tools of analysis, and improved integration of all elements of manufacturing operations, including machines, information and humans. Through this domain, CPSE serves several process industries such as bulk chemicals (including petrochemical and oil & gas), pharmaceuticals & agrochemicals, specialty chemicals, and biofuels.

Integrated Water Networks for Freshwater MinimizationCheng Seong Khor, Benoît Chachuat, Nilay ShahDue to the high demand for freshwater by the process industries, together with the drive for achieving sustainable development, water network synthesis problems have received increasing attention in the PSE community. For the objective of minimizing freshwater use and wastewater generation, water can be reused by channeling the effluent from a water-using operation to other operations, and possibly recycled to the operations where it was generated. In further reducing freshwater and wastewater flowrates after exhausting recovery opportunities via direct reuse/recycle, water regeneration can be considered, which involves performing partial treatment on the effluent by using water treatment and purification units such as membranes and steam stripping prior to reuse/recycle.

CPSE is investigating the synthesis of optimal water networks in the `environomic’ sense – that is, maximizing economic profit and meeting certain environmental sustainability criteria at the same time – while complying with constraints on the water users and/or final discharge limits to the environment. Our focus has been on using superstructure optimization together with realistic regenerator models, which leads to challenging, nonconvex MINLP models. Industrial case studies of water networks in petroleum refineries with a large number of wastewater sources and sinks as well as multiple regenerators have revealed that state-of-the-art global optimization technology can be applied to tackle these problems rigorously, leading in certain cases to more than 50% annual savings in freshwater use. Our recent work has investigated the problem of integrated water network synthesis under uncertainty, with risk management using the Conditional Value-at-Risk (CVaR) metric. It

has been established that rigorous, risk-averse solutions can be computed in reasonable time too, which could make them the solution of choice in planning and decision making.

Figure 1: Principle of two-stage stochastic methodology for water network synthesis under uncertainty.

Figure 2: Histograms comparing the projected total annual cost distributions of risk neutral and risk-averse solutions for a water network consisting of 7 water-using operations, 3 sources and 3 sinks; the regeneration technologies considered for abatement of oil & grease and suspended solids are carbon filter and reverse osmosis.

Application Domain Chemical Manufacturing Systems

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Towards Membrane Cascades for Isothermal Refining Vincentius Surya Kurnia Adi, Marcus Cook, Ludmila Peeva, Andrew Livingston, Benoît Chachuat Crude oil refining is the second most energy-intensive industry after the chemical industry in advanced economies. Current refinery technology is based on distillation, which typically accounts for over half of the total energy consumption due to vaporization (phase change) and the need for reflux. Membrane technology offers a promising alternative for separating mixtures without the need to employ energy intensive operations based on phase change. In particular, organic solvent nanofiltration (OSN) provides a means for separating organic-organic mixtures such as crude oil. In many cases, a mixture separation may not be achieved through a single membrane pass because OSN membranes are not selective enough between the different constituents. Instead, the mixture can be processed through multiple membranes and/or using multiple passes, namely a membrane cascade arrangement.

Given the recent advances in the development of membranes for organic mixtures and their applications in membrane cascades, this project is concerned with the possible use of membranes for hydrocarbon mixtures. We are developing a superstructure optimization approach based on mixed-integer nonlinear programming (MINLP) to determine the most promising cascade configurations. The aim of the optimization is to determine the cascade design and operating conditions maximizing product purity, for a given composition of the inlet stream. Our initial focus is on a binary system of heptane and hexadecane to mimic the light-key and heavy-key in the multicomponent environment of a representative petrochemical/hydrocarbon feed stream while simplifying the analysis.

Figure 3: Optimized lab-scale membrane cascade for purification of heptane from a 50-50 wt% mixture of heptane and hexadecane, using a maximum of 10 identical membrane units, each with an

effective area of 14 cm2

Economically Optimal Integrated Process and MPC Control DesignFlávio Strutzel; David Bogle, CAPES

Figure 4: Benefits of MPC

The use of MPC (Model Predictive Control) is nowadays ubiquitous in the chemical industry and offers great advantages. The zone constrained MPC with economic optimization capabilities is today’s standard in the chemical industry. MPC reduces process variability and enables operation with lower quality giveaway, increasing output of high value added products and decreasing by-product output. However, new chemical processes are being projected without taking into account how design choices affect the MPC’s ability to deliver better control and optimization. Therefore, a methodology to determine if a certain design option favours or hinders MPC performance is desirable.

This project develops the “economic MPC optimization index”, whose intended use is to provide a procedure to compare different designs for a given process, assessing how well a given flowsheet interacts with a generic MPC package. This index is impacted by process controllability, control resilience, control requirements and restrictions of a given plant. It quantifies the economic optimization benefits available and how well the plant performs under MPC control, thereby providing a monetization measure of expected control performance.

This approach assumes the availability of a linear state-space model valid within the control zone defined by the upper and lower bounds of each controlled and manipulated variable. Process economics provides the basis for the analysis as the index needs to be minimised in order to find the most profitable steady state within the zone constraints towards which the MPC is expected to direct the process. Special attention is paid to the effect of model uncertainty and/or disturbances on the index, which may reduce profitability by restricting the ability of a MPC to reach dynamic equilibrium near process restrictions, thus increasing product quality giveaway and costs in turn. This approach has been demonstrated the case study of a realistically sized crude oil atmospheric distillation plant consisting of four alternative designs.

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Figure 5: Illustration of the ‘economic MPC optimization index’ methodology for comparison of alternative process designs.

Sample Workflow – Oil Distillation Case Study

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The Molecular Systems Engineering (MSE) group has over 30 staff and students and, since its inception, has published close to 200 papers many of which have received large numbers of citations in the academic press. The team has expertise in both molecular modelling and thermodynamics and process systems engineering. Their modelling work covers all scales from sub-atomic (quantum) to macroscopic. The group has a website (http://molecularsystemsengineering.com) where it is possible to access recent papers and results.

MSE research is underpinned by a £1.8M Platform Grant (EPSRC) which supports the next generation of post-doctoral researchers and has the support of BMS, Chemistry Innovation, GSK, P and G and Syngenta. The programme is entitled ‘Molecular systems Engineering of High-Value Structured and Formulated products’. The aim is to advance the tools of molecular systems engineering to tackle some of the key molecular challenges to improving the productivity of drug discovery and processing by improving our predictive capability of the relevant physical properties.

MSE collaborates with industry across a broad range of sectors from pharmaceuticals to oil and gas. The following highlights some of our recent publications and progress.

SAFT developments

Figure 1: Statistical associated fluid theory (SAFT) is fundamental to the group’s work.

Two recent papers highlight advances in developing intermolecular potential models for use with the SAFT-VR Mie equation of state and development of force-field parameters from the SAFT-γ Equation of State for use in course-grained molecular simulations.

Developing intermolecular-potential models for use with the SAFT-VR Mie equation of state A major advance in the statistical associating fluid theory for potentials of variable range (SAFT-VR) has recently been made with the incorporation of the Mie (generalized Lennard–Jones [LJ]) interaction between the segments comprising the molecules in the fluid (Lafitte et al. J. Chem. Phys. 2013;139:154504). The Mie potential offers greater versatility in allowing one to describe the softness/hardness of the repulsive interactions and the range of the attractions, which govern fine details of the fluid-phase equilibria and thermodynamic derivative properties of the system. In our current work, the SAFT-VR Mie equation of state is employed to develop models for a number of prototypical fluids, including some of direct relevance to the oil and gas industry: methane, carbon dioxide and other light gases, alkanes, alkyl benzenes, and perfluorinated compounds. A complication with the use of more-generic force fields such as the Mie potential is the additional number of parameters that have to be considered to specify the interactions between the model molecules, leading to a degree of degeneracy in the parameter space. A formal methodology to isolate intermolecular-potential models and assess the adequacy of the description of the thermodynamic properties in terms of the complex parameter space is developed. Fluid-phase equilibrium properties (vapour pressure and saturated-liquid density) are chosen as the target properties in the refinement of the force fields; the predictive capability for other properties such as the enthalpy of vaporization, single-phase density, speed of sound, isobaric heat capacity, and Joule–Thomson coefficient, is appraised. It is found that an overall improvement of the representations of the thermophysical properties of the fluids is obtained using the more-generic Mie form of interaction; in all but the simplest of fluids, one finds that the LJ interaction is not the most appropriate. An update of our work in this area is found in Dufal et al. AIChE J 61 2891 (2015) and Sadeqzadeh et al., Fluid Phase Equilib. 407, 39 (2016).

Application Domain Molecular Systems Engineering

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Force-Field Parameters from the SAFT-Equation of State for Use in Coarse-Grained Molecular Simulations A description of fluid systems with molecular-based algebraic equations of state (EoSs) and by direct molecular simulation is common practice in chemical engineering and the physical sciences, but the two approaches are rarely closely coupled. The key for an integrated representation is through a well-defined force field and Hamiltonian at the molecular level. In developing coarse-grained intermolecular potential functions for the fluid state, one typically starts with a detailed, bottom-up quantum-mechanical or atomic-level description and then integrates out the unwanted degrees of freedom using a variety of techniques; an iterative heuristic simulation procedure is then used to refine the parameters of the model. By contrast, with a top-down technique, one can use an accurate EoS to link the macroscopic properties of the fluid and the force-field parameters. We discuss the latest developments in a top-down representation of fluids, with a particular focus on a group-contribution formulation of the statistical associating fluid theory (SAFT-γ). The accurate SAFT-γ EoS is used to estimate the parameters of the Mie force field, which can then be used with confidence in direct molecular simulations to obtain thermodynamic, structural, interfacial, and dynamical properties that are otherwise inaccessible from the EoS. This year we have advanced in this area, presenting coarse grained (CG) for water (Lobanova et al., Molecular Physics 113, 1228 (2015)); natural gases and condensates Herdes et al., Fluid Phase Equilibria 406, 91 (2015); suprespreading surfactants (Theodorakis et al., Soft Matter 11, 9254 (2015).

Applications– Solvent design for separation The group has carried out a series of studies on, in particular, the separation of carbon dioxide from methane.

A Hierarchical Method to Integrated Solvent and Process Design of Physical CO2 Absorption Using the SAFT-γ Mie Approach Molecular-level decisions are increasingly recognized as an integral part of process design. Finding the optimal process performance requires the integrated optimization of process and solvent chemical structure, leading to a challenging mixed-integer nonlinear programming (MINLP) problem. The formulation of such problems when using a group-contribution version of the statistical associating fluid theory, SAFT-γ Mie, to predict the physical properties of the relevant mixtures reliably over process conditions is challenging. To solve the challenging MINLP, a novel hierarchical methodology for integrated process and solvent design (hierarchical optimization) is presented. Reduced models of the process units are developed and used to generate a set of initial guesses for the MINLP solution. The methodology is applied to the design of a physical absorption process to separate carbon dioxide from methane, using a broad selection of ethers as the molecular design space. The solvents with best process performance are found to be poly(oxymethylene)dimethylethers. A review of the results is presented in J. Bruger et al. AIChE J6,1 3249 (2015).

The separation of carbon dioxide from gas streams is of significant importance in many energy development schemes. Further information is included in the Energy Systems Engineering section of this report.

– Pharma – partitioning of APIs between solvents Many APIs have low solubility in both water and other solvents and it is also difficult to predict partitioning between two solvents.

Good progress has been made at modelling some of these systems. The figure shows the actual and the calculated solubility of ibuprofen and ketoprofen in water and acetone and shows that the models can achieve good agreement with measured values.

Figure 2: Solvent design for seperations and reactions

When looking at systems where there are large numbers of potential solvents and extremely large numbers of potential solvent mixtures, computing time becomes a key factor for modelling. This can be managed by developing generic mathematical formulations of the mixture design challenge and then investigating the most effective solution strategies. Systems that have been studied include mixtures of solvents to maximise ibuprofen solubility and mixtures of solvents that give best performance for the extraction of acetic acid from water.

Similar issues occur when looking at how solvent selection can be used to maximise the reaction rate constant. To optimise it is essential to be able to consider a wide range of solvents (through Computer Aided design techniques), be able to make reliable predictions of kinetics using Quantum mechanics and, finally, integrate within process design by use of Mixed Integer Nonlinear Programming.

In an example case it was possible to increase the rate constant by 126% for the Menshutkin reaction of phenacyl bromide and pyridine and to verify this result experimentally.

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Biological Systems Engineering at CPSE is concerned with the elucidation and control of biological systems at multiple scales ranging from the molecular to the cellular to the tissue to the organ level and beyond. A range of approaches is developed and deployed for this purpose including different kinds of mathematical modelling, analysis, design, optimization and control, and experiments and their integration. The applications of this work span biomedical engineering, biotechnology and systems and synthetic biology. Snapshots of the work in biological systems engineering are presented below, revealing multiple facets of the work in this area.

Dr Misener, Professor Mantalaris, Professor Pistikopoulos and collaborators have developed a novel 3-D biomimetic bioreactor for growing red blood cells ex vivo. The bioreactor recapitulatesarchitectural and functional properties of erythrocyte formation, reducing the need for expensive growth factors by an order of magnitude. Building on this, ongoing work involves developing aglobal superstructure optimization for improved bioreactor design. Another project is motivated by the treatment protocols in Acute Myeloid Leukaemia, which relies on cell cycle phase-specificchemotherepeutic drugs. A platform is developed combining experiments, modelling of the cell cycle, and modelling of cell populations using population balance models. This platform can be the basis of improving chemotherapy planning through such cell cycle phase-specific drugs, leading to optimizing drug dosages and timings in a systematic manner. Overall, these projects involve acombination of mechanistic mathematical modelling, in some cases at multiple levels, design and optimization.

Dr. Kontoravdi and co-workers are developing process models to enable the implementation of Quality by Design in bioprocessing. Model development centres around two main themes: the mechanisms involved in protein glycosylation and the release of host cell contaminants. Protein glycosylation is a type of non-template modification that affects the efficacy, stability and immunogenicity of therapeutic proteins. It is, in turn, affected by process conditions, cell metabolism and intracellular regulation events. The group is working towards understanding these interactions and eventually providing a platform for glycosylation optimisation and control with a view to producing a narrow and targeted set of structures. In parallel, Dr. Kontoravdi is collaborating with Prof. Shah and colleagues in Chemistry and Life Sciences on the design and fabrication of a synthetic enzymatic reactor that will perform protein glycosylation ex vivo in a fully controlled manner. In the second theme, the release of

host cell contaminants is a poorly understood process that largely depends on process conditions and cell health. The group is currently focused on developing a mechanistic understanding of the contaminants content with respect to process conditions and linking this knowledge to the efficiency of the primary purification step, affinity chromatography. Overall this work involves mechanistic mathematical modelling of the relevant cellular biochemical steps and their effect at the process level, with associated tools of analysis and design.

Professor Bogle along with colleagues at the UCL Institute for Liver and Digestive Health have used process systems engineering approaches and tools to tackle medical problems which involve complex chemical transformations and spatial phenomena looking in particular at the liver system, the body’s chemical factory. This involves modelling distributed behaviour necessary to predict the behaviour of drugs for treating liver disease. The model developed has been used to predict the effects of suppression of de novo lipogenesis, stimulation b-oxidation and a combination of the two.

In non-alcoholic fatty liver disease (NAFLD), lipid build-up and the resulting damage is known to occur more severely in perivenous cells. Due to the complexity of studying individual regions of the sinusoid, the causes of this zone specificity and its implications on treatment are largely ignored. A computational model of liver glucose and lipid metabolisms has been developed which treats the sinusoid as the repeating unit of the liver rather than the single hepatocyte. By simulating insulin resistance (IR) and high intake diets leading to the development of steatosis in the model, the work identifies key differences between periportal and perivenous cells accounting for higher susceptibility to perivenous steatosis. Secondly, variation between individuals is seen in both susceptibility to steatosis and in its development across the sinusoid. Sensitivity analysis was used to identify the processes which have the largest effect on both total hepatic triglyceride levels and on the sinusoidal location of steatosis. Results confirm phenomena seen in vivo. Overall, this work involves multiscale and multilevel modelling, and systems engineering tools for their analysis.

Work in Dr Krishnan’s group focuses on information processing in cells and tissues using a combination of mathematical modelling across a range of scales and levels, theoretical and systems analysis, and collaboration with experimentalists. Recent work has focused on information processing in multisite phosphorylation, connecting the

Application Domain Biological Systems Engineering

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enzymatic mechanism to the molecular information processing behaviour. This in turn plays an important role in signalling networks, where such enzymatic mechanisms are implicated. Another project in the area of mRNA translation combines experiments (in the group of Ian Stansfield) and modelling to develop a systems analysis for connecting ribosomal recycle, feedback, nonsense mediated decay and mRNA stability. A complementary approach in this area has been to develop new Probabilistic Boolean Network tools to facilitate analysis of these stochastic transport models. At the network level, recent work has focused on the effects of spatial regulation and compartmentalization in biochemical networks, an aspect of increasing importance in both systems and synthetic biology. Another project examines the effect of dynamic environments on the progression of the cell cycle in budding yeast. Using a multiplicity of models, as well as different experimental data, a number of underlying features of cell cycle progression in dynamically varying environments has been demonstrated. A platform for connecting the effects of the environment, the cell cycle and growth has also been created. Finally, at the cell and tissue levels the effects of different modes of intrinsic and induced drug resistance mechanisms in tumours at the cellular and tissue levels has been studied. This work clearly demonstrates the need to account for both cellular and tissue

levels simultaneously, in a systematic manner in this context. Overall, the projects described above involve a combination of mathematical models (temporal, spatial, stochastic) and tools from nonlinear dynamical systems analysis, systems and control engineering and networks for analysis.

Taken together, the above research snapshots clearly demonstrate a number of features. Firstly, biological systems are complex in many ways and present a range of challenges at different scales. Secondly, systems engineering approaches are essential to tackle these challenges, and further different kinds of systems engineering tools are needed in different contexts. Thirdly, a combination of modelling, experiments and the deployment of appropriate systems engineering tools can prove to be very effective. Fourthly, new systems engineering approaches need to be developed in certain cases. Finally, systems engineering provides vital input in the life sciences in areas ranging from basic biology, biomedical engineering, biotechnology and synthetic biology. All these areas in turn provide new impetus for systems engineering itself.

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The importance of Energy Systems Engineering as an application domain within CPSE has increased over the last few years. Concerns over the cost and integrity of supply, coupled with the apparent inability to control greenhouse-gas emissions resulting from the increased use of fossil fuels, has amplified the need to focus not only on a less carbon-intense supply but the efficiency of energy generation and use together with strategies for carbon mitigation.

CPSE is engaged in a number of these areas of research including Urban Energy Systems, Bioenergy Systems, Hydrogen Networks and Polygeneration, Energy Storage, Carbon Capture and Storage, and Network Systems.

Urban Energy Systems Cities use up approximately three-quarters of the world’ s energy and play a major role in issues such as economic security and climate change. Work continues in the area of Urban Energy Systems, building on the £4 million, 5-year collaborative project with BP that investigated the technologies and systems used in cities to distribute and consume energy. Understanding these systems in more detail can provide valuable insights into how to make the distribution and consumption of energy more cost effective and sustainable in cities in the future. State of the art Urban Energy Systems Model (URBEN) is a comprehensive optimisation tool that enables urban planners, property developers and equipment manufacturers to determine the optimum mix of technologies in order to meet policy goals and cost constraints for both retrofit and new urban build projects.Research continues on new approaches to designing our urban energy infrastructure so that it is more efficient and has less impact on the environment. (Shah, Kierstead)

Molecular Energy Systems Energy is a key area in which Molecular Systems Engineering approaches have been developed and applied to key problems. The general approach is to develop molecular equations of state for phase behaviour and thermodynamic properties and integrate these into process system design and optimisation approaches, using for instance gPROMS, for combined fluids/materials and process design. A good recent example of this involves an integrated molecular and process design of separation of carbon dioxide from natural gas (methane) for well-head applications.Here we have used our group contribution SAFT-γ Mie approach to design new solvents for CO2/methane separation using a unified process/solvent

optimisation of the process. Similar approaches are being applied to high-pressure amine solvent design for separation with membrane contactors. The other main line of work involves addressing climate-change mitigation issues: integrated solvent and process design of carbon dioxide capture from power station flue gas at low pressures. With a detailed SAFT description of the thermodynamics of the reactive dissolution equilibria we can successfully model the process by focusing on the mass transport with just a single transferable modulation of the diffusivity of carbon dioxide in the solvent. (Jackson, Adjiman, Galindo, Pantelides)

Energy Storage We are modelling integrated energy systems for off-grid mining operations to identify the trade-offs between reliability of energy provision, due to the use of variable renewable energy generation such as solar and wind, with the cost of large scale energy storage. The system model includes the variable and stochastic behaviour of renewable energy. Storage technologies include compressed air, molten salts and pump-hydraulic systems with energy efficiency and losses. The approach includes the use of case studies of large scale mining operations with both heat and power demands in Chile and Canada. (Fraga)

Local Energy Systems This area involves the design of neighbourhood-level energy systems, incorporating local distribution and sharing of both heat and power amongst dwellings. Local energy generation includes combined heat and power units, such as fuel cells using grid supplied gas, solar thermal, solar photo-voltaic and wind turbines. Energy storage in the form of hot water tanks is included. A key consideration is the regulatory framework to support energy integrated at this neighbourhood scale and the impact of such regulations on the systems design. (Fraga)

Nuclear Reprocessing Recently research has started on looking at the design of nuclear reprocessing using intensified operations. Traditional technologies for separation are mixer-settlers; we are looking at micro-channels for intensified operations to reduce the volume of solvents required and improve the separation performance. (Fraga)

Application Domain Energy Systems Engineering

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Multiscale Modelling of Integrated Energy Systems There is a strong CPSE engagement (Mac Dowell, Shah, Maitland) within the CleanFAB (Clean Fossil and Bioenergy) Group, an interdisciplinary team of researchers studying how fossil fuels and bioenergy, in conjunction with CCS, will be key to enabling our stable, cost-effective transition to a low-carbon energy system. From engineering to economics, we are determined to make this adaptation as successful as possible. The work focuses on the multi-scale modelling of clean fossil and bioenergy as part of the diverse energy system of the 21st century. An example of the work we are carrying out in this space is the MESMERISE-CCS project wherein we are integrating energy system, electricity market, CCS-power plant, CO2 transport and CO2 storage models. This work is driven by the view that the role that thermal power plants will play in the energy system going forward will be distinct to that which they played historically. In particular, the concept of baseload or indeed mid-merit power plants will be a thing of the past– in order to be successful, thermal power plants will need to operate in a much more flexible fashion than in the 20th century. The objective of this work is therefore to understand how flexible the CCS chain needs to be, to identify the flexibility-limiting links in the CCS chain and to gain insight into the value of re-engineering these systems to provide enhanced flexibility to the energy system, thus enabling the integration of increased quantities of renewable power, hastening our transition to a low-carbon energy system. (Mac Dowell)

Carbon Storage The Qatar Carbonates and Carbon Storage Research Centre (QCCSRC) is a 10 year, $70m research programme funded by Qatar Petroleum, Shell and Qatar Science and Technology Park. It is the largest industry-funded research programme at Imperial and aims to provide the underpinning science and engineering to enable the optimised design and operation of large-scale carbon dioxide storage operations in carbonate reservoirs typically found in Qatar and other parts of the Middle East.

The activity is a close collaboration between the Departments of Chemical Engineering and Earth Science and Engineering and involves the close interplay of experimental and theoretical/numerical modelling research. Molecular Systems Engineering and Multiscale Modelling within CPSE are a key part of this activity and the programme has enabled a unique partnership of modelling and experimental work, the one driving the other in terms of new insights and improved predictive capability.

The experimental work involves characterisation of the rocks, the properties of reservoir fluids mixed with supercritical CO2 and the multiphase flow of such fluids in the porous and fractured carbonate rocks. Imaging using X-ray micro-tomography and modified body-scanners plays a major role in this. The modelling work comprises prediction of the thermophysical properties (phase behaviour, interfacial properties, transport properties) of the fluids involved under high temperature-pressure reservoir conditions. Molecular Systems Engineering plays a major role here, and new developments of the SAFT approaches, are transforming our ability to predict accurately the way complex fluid mixtures behave under such extreme conditions. These models feed into simulations of multiphase fluid flow in the storage rocks on a wide range of length-scales, from the pore scale (pore network models and Lattice Boltzmann) through core and metre block scales up to the kilometre distances of CO2 plume development at the reservoir scale. Once robust reservoir models are developed, the challenge will be to use systems engineering approaches to aid in the design, optimisation, monitoring and control of these complex operations. (Maitland, Jackson, Galindo)

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The application of system engineering techniques to environmental problems is relatively nascent within CPSE, but is a rapidly emerging area. The dynamics of the interactions, in both length- and time-scales, between human-natural systems are complex and nuanced, often involving multiple stakeholder groups. Thus the tools and techniques developed within CPSE are ideally poised to make a sizable contribution to this emerging area, in the context of process and systems optimisation and also in the provision of decision support tools to the industrial and policy-making communities.

Plant-wide Optimization of Full-Scale Wastewater Treatment Plants Improving operational and process control strategies has become key for the sewage industry to reduce their energy consumption without compromising effluent quality. These strategies may be particularly useful for energy-intensive processes such as activated sludge aeration, which can account for 45-75% of a plant’s energy expenditure. Overall, it is estimated that energy consumption of most wastewater treatment plants (WWTPs) may be reduced by 10-40% this way. Nevertheless, WWTPs are comprised of a large number of treatment and separation units, which involve a great variety of processes acting on different time scales and interacting with each other via recycling loops. Failure to account for these interactions, e.g., by optimizing in a unit-wise manner, may not lead to the largest possible improvements and could even be detrimental from a plant-wide standpoint.

The group of Dr Chachuat is working on the development and application of a model-based methodology in order to provide a better understanding of the impacts of changing effluent quality targets on plant-wide energy use and fugitive emissions. Two industrial case studies corresponding to existing activated sludge plants (including

sludge treatment), owned and operated by Sydney Water (Australia), were investigated. Plant-wide dynamic models were assembled and calibrated using historical data for both plants, paying special attention to closing the solids balances in the main treatment/separation units. A scenario-based optimization approach was used in an objective to determine the best possible performance with respect to a variety of economic and environment sustainability metrics. In turn, these results could feed into decisions revolving around treatment-plant operation and asset management as well as inform the next major plant license review. An inherent advantage of this methodology is that it can be used for analysing other ‘what-if’ scenarios or for assessing the performance of other WWTPs.

Figure 1: Comparison of various strategies for an optimal interplay between plantwide power consumption and NO3 emissions in the treated effluent

Application Domain Environmental Systems Engineering

Figure 2

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Multi-Scale Modeling of Microalgae Culture for Optimization and ControlAndreas Nikolaou, Benoît Chachuat Microalgae have long been identified as a promising candidate for biofuel production. These microorganisms have fast growth rates and a rich protein content, in addition to being able to produce and accumulate lipids under certain stress conditions. They are considered by many to be a viable alternative to conventional oil crops due to a higher biomass productivity and independence towards arable land and fresh water. Moreover, the downstream processing of microalgae in biorefineries opens the perspective for producing a wide spectrum of valuable products in addition to biofuel, including cosmetics, pharmaceuticals and nutraceuticals, while treating nutrient-rich effluents from wastewater treatment works or CO2 from power-plant flue gas, all in the same process. Despite these promises, mass production of microalgae for large-scale biofuel production is yet to be demonstrated, especially in regards of their high nutrient requirements, the trade-off between biomass growth and lipid productivity, and the lipid extraction challenges.

The group of Dr Chachuat is working on the development of mathematical models capable of capturing the processes governing light-limited growth in microalgae. Particularly important in outdoor culture systems, where the light irradiance vary greatly, are the mechanisms of photoinhibition and photoacclimation, which act on a wide range of time-scales (from seconds to days). Our recent focus is on integrating microalgae growth models at the cell level with CFD and light attenuation models describing the mixing conditions and the vertical light distribution in raceway ponds and other cultivation systems. These models provide a way of assessing various scale-up effects and how certain key parameters may affect microalgae productivity. The ultimate goal is to provide reliable predictions in large-scale production systems, as a means for optimizing their design and operation. This work is a collaboration with the University of Padova (Prof. Bezzo, Prof. Morosinotto) and BIOCORE-INRIA (Dr. Bernard).

Water and Energy Systems in Sustainable City Development – Resilience.IO platform The grand challenges facing human societies are closely interconnected with the sustainable provisioning of energy, water and material resources, for growing and developing populations, and the subsequent processing and management of waste and pollution. Current urban water and energy systems are expanding increasing attention paid to their economic and environmental impacts. However, there is a lack of a sufficiently systematic approach to address these impacts and evaluate optimal strategies, either in the context of research or real-world decision making.

The group of Professor Nilay Shah took advantage of their strength in urban energy and transportation systems to expand the study to water, sanitation, and hygiene sector (WASH). The current regional demographics, land-use, infrastructure and economic information is used as input for the initial state of the focused urban system incorporating energy, water and other related resources.

Detailed spatio-temporal demand data, obtained by simulating a synthetic population using agent-based models, is further used to plan capacity utilization and expansion by supply-side matching on a cost optimal basis, eventually aiming to explore the optimal design and operational strategies for residential, commercial, industrial, and other sectors. Moreover, long-term socio-economic scenarios are addressed in the urban system development through a real-time feedback loop.

The team developed a prototype based on the Greater Accra Metropolitan Area (GAMA) city-region in Ghana, as part of the Department for International Development (DfID) funded Future Cities Africa (FCA) project. The outputs depict an overall resource landscape of the studied urban area, but also provide the material and energy balance of supply and demand from both macro and micro perspectives, which is used to propose environmentally friendly and cost effective sustainable city-development strategies. This work is to become a core component of the Resilience.io platform as an open-source, data-driven, integrated systematic tool gathering social, environmental and economic data to inform urban planning, investment and policy-making for city-regions globally.

Figure 3 (right and left plots): Velocity field in raceway pond (left plot) and simulated microalgae production over several weeks (right plot)

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Figure 4: Example of simulated wastewater flow in GAMA (top plot) and optimized investment strategies for water and wastewater technologies (bottom plot)

Model Predictive Control of Post-Combustion CO2 Capture Process integrated with a power plantThe process of CO2 capture and storage is a potential way to control the emissions of CO2 from large-scale power plants. A favoured CCS (Carbon Capture and Storage) strategy is the post-combustion CO2 capture process using MEA. However, in a gas-fired power station, the power plant has to respond to dispatching signals from the transmission operator in order to provide load balancing. Frequent changes in operating point create significant disturbances to the CO2 capture plant. Therefore, the integration of the CO2 capture process and gas-fired power plants will increase the need to design advanced model-based control systems to overcome the process interactions and maintain dynamic operability of power plant and CCS unit. The dynamic behaviour of the capture plant was implemented in gCCS [1], a tool developed within gPROMS for the modelling of the capture plant units. In order to show how the proposed control scheme responds to a real operation during a day, fluctuation of the flue gas flowrate was implemented in the model. A Model Predictive Control (MPC) strategy was implemented in Matlab in order to maintain the dynamic operability of the CO2 capture plant in the presence of

changes in the load [2]. In order to implement the MPC control strategy, the detail dynamic model of the capture unit was approximated by a state-space model of five inputs and five outputs. A key advantage of the MPC control scheme is that it uses an optimisation framework which makes use of explicit process models to predict the future behaviour of the plant. The results demonstrated that the MPC control strategy can compensate for disturbances. Moreover, the work also studied flexibility scenarios involving changes to the set point for the carbon capture rate thus allowing an economic trade-off between use of steam (and the consequent increase in use of natural gas) versus decreased capture rate which could incur penalties for CO2 emissions. The work was funded by EPSRC through grant EP/J020788/1 Gas-FACTS: Gas – Future Advanced Capture Technology Options.

Understanding Methane and Carbon Dioxide Emissions from the Natural Gas Supply Chain When you compare natural gas to other fossil fuels such as coal, its combustion generates approximately half as much carbon dioxide (CO2) emissions. However, natural gas is also mainly composed of methane, which is itself a strong greenhouse gas, and is emitted at different stages along the natural-gas supply chain. While methane dissipates from the atmosphere more quickly than CO2, it is considered to have a higher global warming potential and therefore a more potent short-term effect on climate change than carbon dioxide.

The big question is: do these methane emissions along the supply chain undermine natural gas’s lower carbon credentials? Over the last five years, a large number of studies have estimated how much methane is emitted through the whole natural-gas supply chain from exploring, extracting, producing, processing and transporting natural gas. These studies have used a variety of methods to understand the issue, but so far have differed significantly in their findings.

Professor Nigel Brandon and Dr Adam Hawkes and colleagues at the Sustainable Gas Institute (SGI) have undertaken a comprehensive review of all the available global data on both CO2 and methane emissions from the natural-gas supply chain to fully understand the scale of the issue. This briefing note summarises the main findings and recommendations of the Institute’ s first White Paper. By systematically assessing the literature in terms of transparency, relevance and accuracy, the paper assembles and analyses the current state of our knowledge on emissions globally.

Key Questions• How much methane and CO2 is emitted from the natural

gas supply chain? • What methods are being used to estimate these emissions? • What factors affect emission ranges? • Why do we see such a big range?

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This review analysed over 250 studies and reports. These studies covered natural gas from both conventional wells and unconventional wells at every stage in the supply chain, as well as examining the liquefied natural gas (LNG) process.

KEY FINDINGS: 1. The range of estimated emissions across the supply chain is vast. • Combined methane and CO2 emissions from the supply chain

are between 14 and 302 gCO2eq/kWh • A small number of studies estimate exceptionally high emissions

from specific supply chain stages or facilities. However, the average estimates lie towards the lower end (see Figure 5).

• Methane emissions are estimated to be between 0.2% and 10% of total produced methane.

2. Key emissions sources are during well completions, liquids unloading, and the use of pneumatic devices and compressors.• Studies show that the use of Reduced Emission Completions

(RECs) equipment can significantly reduce methane emissions by over 75%. This technique is now compulsory in the United States.

• Emissions from both unconventional and conventional wells are comparable as long as methane is captured rather than flared during well completion.

• Gas venting and leakage from compressors and pneumatic devices across the supply chain contribute significantly to emissions.

• More research is needed to quantify the factors affecting the emissions from the liquids unloading process.

3. There is evidence of ‘super emitter’ facilities all along the supply chain. • A small number of high-emitting facilities strongly impact the

emissions profile at every stage in the production process. • These may be a result of the use of ineffective process

equipment and poor operational and maintenance strategies, and could be eliminated and reduced if the best available techniques were applied.

4. Some of the emissions estimates are considerable, but there is potential to reduce these emissions. • If modern equipment with appropriate operation and

maintenance regimes were to be used, the total supply chain emissions should lie within the range of 19–212 gCO2 eq/kWh with a central estimate of 92 gCO2 eq/kWh. If the natural gas was used in a power plant, these supply chain emissions would contribute between 4%–35% of the total greenhouse gas emissions per kWh of electricity generation.

• Methane emissions are expected to be 0.3%–2.4% of total produced methane, with a central estimate of 1.4%.

• Further reductions could be made, particularly for emissions from transport, storage and distribution, and also at the point when gas is extracted.

5. A wide variety of techniques are used to monitor emissions which means supply chain emissions estimates vary greatly in the literature. • Many studies apply a top-down approach to measuring

methane emissions which involves measuring or inferring the concentration of methane in the atmosphere within a region, and then attributing emissions to specific sources within that region. A more thorough approach would involve a bottom-up point measurement at specific places on the ground in combination with local leak detection.

• Methodological assumptions vary significantly across the literature and have a major effect on the estimated emissions (e.g., total production volume of a well and the assumed methane content of the extracted natural gas).

6. There is a significant lack of data, particularly for regions other than the US.• More data are required globally for offshore extraction, coal-bed

methane extraction, liquids unloading, well completions with RECs, transmission and distribution pipelines, and methane emission measurement from all LNG stages.

7. Further research is needed to determine the potential role of natural gas in a low-carbon energy mix. • Research exploring the technological, operational or regulatory

mechanisms is required to achieve emission reductions. • Further studies are also necessary to quantify the potential

reduction in supply-chain emissions and to examine factors affecting different supply-chain emissions in order to understand the mitigation potential at each stage and also to look at the impact of regional regulation (e.g., regulation for continuous monitoring of ‘super-emitting’ facilities).

References[1] Process Systems Enterprise, 2015, gCCS – overview: whole chain CCS systems modelling, on-line February 2016, http://www.psenterprise.com/power/ccs/gccs.html[2] Mehleri ED, Mac Dowell N, Thornhill NF, 2015, Model predictive control of post-combustion CO2 capture process integrated with a power plant, 12th International Symposium on Process Systems Engineering (PSE) / 25th European Symposium on Computer Aided Process Engineering (ESCAPE), Publisher: ELSEVIER SCIENCE BV, Pages: 161-166

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Application Domain Supply Chains of the Future

Supply chains of the future will have to deal with a host of new challenges facing us in the 21st century, including:• Exploiting new energy and material sources• Cleaner exploitation of existing sources

(e.g. high-carbon fossil fuels)• Resource efficiency to deal with increasing scarcity of non-fuel

resources (e.g. water and minerals)• Decarbonised supply chains• Customisation of products and services (e.g. healthcare) closer

to the point of use.

A key feature of supply-chain optimisation is the need to include multiple objective functions when considering the design or operation of a supply chain. These may reflect for example economics, sustainability and responsiveness metrics. An example of an industrial case study which employs multi-objective optimisation is discussed below.

Incorporating sustainability measures in supply chainsSustainability plays a key role in the management of a successful and responsible business. When trying to improve the sustainability performance of a business, there are three major challenges that need to be addressed. First, assessment of sustainability requires consideration of not just economic, but also environmental and social impacts. Second, we need to find appropriate sustainability indicators and gather the necessary data in order to quantify sustainability performance. Finally, sustainability has to be seen in the context of the whole system, i.e., it has to include all activities along the supply chain. In this work, we consider all three aspects and propose a multi-objective optimisation framework for the optimisation of a sustainable supply chain.

Three sustainability indicators have been considered, namely the total cost (reflecting economics), GHG emissions (reflecting sustainability) and lead time (reflecting responsiveness). We apply this framework to an industrial test case using real-world data drawn from an industrial collaborator. The results show clear trade-offs between the three different objectives. However, we can also observe that typically a considerable decrease in GHG emissions or lead time can already be achieved with only a relatively small increase in cost. The proposed framework enables us to determine such trade-off relations and consequently make decisions that improve the sustainability performance of the supply chain.

Case study and resultsA case study explored the allocation of production of multiple products to seven plants around the world, and their subsequent distribution to markets, using the supply chain structure as below:

R aw materials uppliers

P roductionplants

C us tomerlocations

A trade-off curve between the three objectives was developed by the use of classical multi-objective optimisation procedures. The overall trade-offs between the objectives can be seen below:

64

66

68

70

72

74

76

78

66 68 70 72 74 76

To

tal

GH

G E

mis

sio

n

Total C os t

TLT ≤ 1098

TLT ≤ 1106

TLT ≤ 1113

TLT ≤ 1120

TLT ≤ 1128

TLT ≤ 1165

TLT ≤ 1202

TLT ≤ 1239

TLT ≤ 1276

TLT ≤ 1312

TLT ≤ 1349

TLT ≤ 1386

TLT ≤ 1421

T ota l L e a d T ime

It can be seen that GHG emissions can be reduced considerably without a significant cost increase initially, but then they are very hard to reduce. Shorter lead times can only be achieved by compromising both emissions and cost.

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“CPSE academics are expected to span several disciplines including systems modelling, optimisation and control and computing.”

Academic ProfilesProfessor Berc Rustem

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Nilay Shah FREng

Professor of Process Systems Engineering, Director CPSE, Department of Chemical Engineering, Imperial College London

QualificationsMEng in Chemical Engineering (Imperial College London)PhD in Chemical Engineering (Imperial College London)

Awards and DistinctionsFellow of the Royal Academy of EngineeringFellow of the IChemE RAEng MacRobert Award and Prize (2007) RSC/SCI/IOM Beilby Medal (2005) ICI/RAEng Fellowship (1997-2002) Imperial College Faculty of Engineering Teaching Award (2009) IChemE Hutchison Medal (2012)

Research InterestsDesign and analysis of energy and process systems:• Bioenergy/Biorenewable systems and technologies.• Urban Energy Systems.• Modelling and optimisation of low-carbon technologies and

systems (e.g., CCS, hydrogen infrastructure etc).

Supply-chain design and optimisation:• Development of new algorithms for large-scale supply-chain

models.• Application to sector-specific processes (e.g., pharmaceuticals,

oil and gas, consumer goods)

Process synthesis and development for fine chemicals, pharmaceutical and biochemical processes:

• Combination of chemistry with modelling and engineering to improve process designs and to speed up process development.

• Performing rapid economic assessments for different manufacturing routes.

• Developing long-term capacity and investment plans.

Safety in design and operation, especially the application of formal mathematical techniques to assess and improve process safety

Other ActivitiesCo-founder of Process Systems Enterprise Ltd EPSRC college member EPSRC Manufacturing Strategy Advisory Team BBSRC Industrial Biotechnology and Bioenergy Strategic Advisory Team IChemE Transactions editorial board member Director, Imperial College Manufacturing Futures Lab

Reviewer forAIChE Journal Chemical Engineering Research and Design Computers and Chemical Engineering Chemical Engineering Science A-Star Research Council (Singapore) Science Foundation Ireland

Academic CollaborationsUniversity College London, Department of Chemical EngineeringNewcastle and Strathclyde Universities, CPACT National University of Singapore Delft University of Technology Rothamsted Research IBERS – University of Aberystwyth University of York Aston University Newcastle University Cardiff University

Academic Profiles

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Industrial CollaborationsShell (Energy Efficient Refining) Syngenta (Supply Chain Optimisation) Sainsbury’s (Store of the Future) Unilever (Sustainable Supply Chains Design) Energy Technologies Institute (Bioenergy Value Chains) Biosep (Biomass Fractionation) Petronas (Novel Gas Separation Technologies)

PublicationsJournal Articles (A * indicates open-access publication)1. Voll P, Jennings M, Hennen M, Shah N, Bardow A, 2014, The

Good, the Bad, and Your Real Choices – Decision Support for Energy Systems Synthesis through Near-Optimal Solutions Analysis, Computer Aided Chemical Engineering, Vol: 33, Pages: 25-30, ISSN: 1570-7946

2. Guo M, Richter GM, Holland RA, Eigenbrod F, Taylor G, Shah N, Implementing Land-use and Ecosystem Service Effects into An Integrated Bioenergy Value Chain Optimisation Framework, Computers and Chemical Engineering, ISSN: 1873-4375

3. Al-Ansari T, Korre A, Nie Z, Shah N, 2015, Development of a life cycle assessment tool for the assessment of food production systems within the energy, water and food nexus, Sustainable Production and Consumption, Vol: 2, Pages: 52-66

4. Stockford C, Brandon N, Irvine J, Mays T, Metcalfe I, Book D, Ekins P, Kucernak A, Molkov V, Steinberger-Wilckens R, Shah N, Dodds P, Dueso C, Samsatli S, Thompson C, 2015, H2FC SUPERGEN: An overview of the Hydrogen and Fuel Cell research across the UK, International Journal of Hydrogen Energy, Vol: 40, Pages: 5534-5543, ISSN: 0360-3199

5. Niu H, Leak D, Shah N, Kontoravdi C, 2015, Metabolic characterization and modeling offermentation process ofan engineered Geobacillus thermoglucosidasius strain for bioethanol production with gas stripping, CHEMICAL ENGINEERING SCIENCE, Vol: 122, Pages: 138-149, ISSN: 0009-2509

6. Ortiz-Gutierrez RA, Giarola S, Shah N, Bezzo F, 2015, An approach to optimize multi-enterprise biofuel supply chains including Nash equilibrium models, 12TH INTERNATIONAL SYMPOSIUM ON PROCESS SYSTEMS ENGINEERING AND 25th EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING, PT C, Vol: 37, Pages: 2255-2260, ISSN: 1570-7946

7. Samsatli S, Samsatli NIJ, Shah N, 2015, BVCM: A comprehensive and flexible toolkit for whole system biomass value chain analysis and optimisation – Mathematical formulation, APPLIED ENERGY, Vol: 147, Pages: 131-160, ISSN: 0306-2619

8. Sharifzadeh M, Richard CJ, Liu K, Hellgardt K, Chadwick D, Shah N, 2015, An integrated process for biomass pyrolysis oil upgrading: A synergistic approach, BIOMASS & BIOENERGY, Vol: 76, Pages: 108-117, ISSN: 0961-9534

9. Sharifzadeh M, Shah N, 2015, Comparative studies of CO2 capture solvents for gas-fired power plants: Integrated modelling and pilot plant assessments, INTERNATIONAL JOURNAL OF GREENHOUSE GAS CONTROL, Vol: 43, Pages: 124-132, ISSN: 1750-5836

10. Sharifzadeh M, Wang L, Shah N, 2015, Integrated biorefineries: CO2 utilization for maximum biomass conversion, RENEWABLE & SUSTAINABLE ENERGY REVIEWS, Vol: 47, Pages: 151-161, ISSN: 1364-0321

11. Sharifzadeh M, Wang L, Shah N, 2015, Decarbonisation of olefin processes using biomass pyrolysis oil, APPLIED ENERGY, Vol: 149, Pages: 404-414, ISSN: 0306-2619

12. Akgul O, Mac Dowell N, Papageorgiou LG, Shah N, 2014, A mixed integer nonlinear programming (MINLP) supply chain optimisation framework for carbon negative electricity generation using biomass to energy with CCS (BECCS) in the UK, INTERNATIONAL JOURNAL OF GREENHOUSE GAS CONTROL, Vol: 28, Pages: 189-202, ISSN: 1750-5836

13. Boot-Handford ME, Abanades JC, Anthony EJ, Blunt MJ, Brandani S, Mac Dowell N,Fernandez JR, Ferrari M-C, Gross R, Hallett JP, Haszeldine RS, Heptonstall P, Lyngfelt A, Makuch Z, Mangano E, Porter RTJ, Pourkashanian M, Rochelle GT, Shah N, Yao JG, Fennell PS, 2014, Carbon capture and storage update, ENERGY & ENVIRONMENTAL SCIENCE, Vol: 7, Pages: 130-189, ISSN: 1754-5692

14. Jennings M, Fisk D, Shah N, 2014, Modelling and optimization of retrofitting residential energy systems at the urban scale, ENERGY, Vol: 64, Pages: 220-233, ISSN: 0360-5442

15. Jennings MG, Shah N, 2014, Workforce planning and technology installation optimisation for utilities, COMPUTERS & INDUSTRIAL ENGINEERING, Vol: 67, Pages: 72-81, ISSN: 0360-8352

16. Khor CS, Chachuat B, Shah N, 2014, Fixed-flowrate total water network synthesis under uncertainty with risk management, JOURNAL OF CLEANER PRODUCTION, Vol: 77, Pages: 79-93, ISSN: 0959-6526

17. Khor CS, Chachuat B, Shah N, 2014, Optimization of Water Network Synthesis for Single-Site and Continuous Processes: Milestones, Challenges, and Future Directions, INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, Vol: 53, Pages: 10257-10275, ISSN: 0888-5885

18. Mac Dowell N, Shah N, 2014, Dynamic modelling and analysis of a coal-fired power plant integrated with a novel split-flow configuration post-combustion CO2 capture process, INTERNATIONAL JOURNAL OF GREENHOUSE GAS CONTROL, Vol: 27, Pages: 103-119, ISSN: 1750-5836 Pantaleo A, Candelise C, Bauen A, Shah N, 2014, ESCO business models for biomass heating and CHP: Profitability of ESCO operations in Italy and key factors assessment, RENEWABLE & SUSTAINABLE ENERGY REVIEWS, Vol: 30, Pages: 237-253, ISSN: 1364-0321

19. Pantaleo AM, Camporeale S, Shah N, 2014, Natural gas-biomass dual fuelled microturbines: Comparison of operating strategies in the Italian residential sector, APPLIED THERMAL ENGINEERING, Vol: 71, Pages: 686-696, ISSN: 1359-4311

20. Pantaleo AM, Giarola S, Bauen A, Shah N, 2014, Integration of biomass into urban energy systems for heat and power. Part I:An MILP based spatial optimization methodology, ENERGY CONVERSION AND MANAGEMENT, Vol: 83, Pages: 347-361, ISSN: 0196-8904

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21. Pantaleo AM, Giarola S, Bauen A, Shah N, 2014, Integration of biomass into urban energy systems for heat and power. Part II: Sensitivity assessment of main techno-economic factors, ENERGY CONVERSION AND MANAGEMENT, Vol: 83, Pages: 362-376, ISSN: 0196-8904

22. Todri E, Amenaghawon AN, del Val IJ, Leak DJ, Kontoravdi C, Kucherenko S, Shah N, 2014, Global sensitivity analysis and meta-modeling of an ethanol production process, CHEMICAL ENGINEERING SCIENCE, Vol: 114, Pages: 114-127, ISSN: 0009-2509

23. Zhang Q, Shah N, Wassick J, Helling R, van Egerschot P, 2014, Sustainable supply chain optimisation: An industrial case study, COMPUTERS & INDUSTRIAL ENGINEERING, Vol: 74, Pages: 68-83, ISSN: 0360-8352

Conference Papers1. Bustos-Turu G, Van Dam KH, Acha S, Shah N 2015,

Estimating plug-in electric vehicle demand flexibility through an agent-based simulation mode

2. lSamsatli S, Samsatli NJ, Shah N, Optimal design of a future hydrogen supply chain using a multi-timescale and spatially-distributed model, Hydrogen & Fuel Cell SUPERGEN Researcher Conference 2014

3. Pantaleo AM, Ciliberti P, Camporeale S, Shah N, 2015, Thermo-economic assessment of small scale biomass CHP: steam turbines vs ORC in different energy demand segments, 7th International Conference on Applied Energy (ICAE), Publisher: ELSEVIER SCIENCE BV, Pages: 1609-1617, ISSN: 1876-6102

4. Brown S, Martynov S, Mahgerefteh H, Fairweather M, Woolley RM, Wareing CJ, Falle SAEG, Rutters H,Niemi A, Zhang YC, Chen S, Besnebat J, Shah N, Mac Dowell N, Proust C, Farret R, Economou IG, Tsangaris DM, Boulougouris GC, Van Wittenberghe J, 2014, CO(2)QUEST: Techno-economic assessment of CO2 quality effect on its storage and transport, 12th International Conference on Greenhouse Gas Control Technologies (GHGT), Publisher: ELSEVIER SCIENCE BV, Pages: 2622-2629, ISSN: 1876-6102

5. Elahi N, Shah N, Korre A, Durucan S., 2014, Multi-period least cost optimisation model ofanintegrated carbon dioxide capture transportation and storage infrastructure in the UK, 12th International Conference on Greenhouse Gas Control Technologies (GHGT), Publisher: ELSEVIER SCIENCE BV, Pages: 2655-2662, ISSN: 1876-6102

6. Korre A, Nie Z, Durucan S, Elahi N, Shah N, Ahmad S, Goldthorpe W, 2014, The effect of market and leasing conditions on the techno-economic performance of complex CO2 transport and storage value chains, 12th International Conference on Greenhouse Gas Control Technologies (GHGT), Publisher: ELSEVIER SCIENCE BV, Pages: 7225-7233, ISSN: 1876-6102

7. Mac Dowell N, Shah N, 2014, Optimisation of post-combustion CO2 capture for flexible operation, 12th International Conference on Greenhouse Gas Control Technologies (GHGT), Publisher: ELSEVIER SCIENCE BV, Pages: 1525-1535, ISSN: 1876-6102

Claire S. Adjiman FREng

Professor of Chemical Engineering, Department of Chemical Engineering, Imperial College London

Qualifications MEng in Chemical Engineering, Imperial College London PhD in Chemical Engineering, Princeton University

Awards and Distinctions Fellow of the Royal Academy of EngineeringFellow of the Institution of Chemical Engineers Chartered Engineer EPSRC Leadership Fellowship, 2012-2017 Henry E. Armstrong Memorial Lecture of the Society of Chemical Industry, 2011 Philip Leverhulme Trust Prize for Engineering, 2009 Research Excellence Award for Molecular Systems Engineering team, Imperial College, 2009 Rector’s Excellence Award, Imperial College, 2007 Royal Academy of Engineering ICI Fellowship, 1998-2003 Porter Ogden Jacobus Honorific Fellowship, Princeton University, 1997

SecondmentsProcess Systems Enterprise Ltd, September 2006-August 2007

Research Interests Systematic methodologies for integrated molecular and process design for reactive processes: development of modelling and optimisation tools and applications (e.g., solvent design for reactions or CO2 capture, risk management). Model-based assessment of design of energy-conversion systems including solid-oxide fuel cells. Development of property-prediction techniques integrating different scales of modelling (from quantum mechanics to advanced equations of state). Global analysis techniques, such as global optimisation and safety analysis

Other Activities Associate Editor, Chemical Engineering Science Associate Editor, Journal of Global Optimization Editorial Board, Fluid Phase Equilibria AIChE: Technical area co-chair/chair for CAST10a, 2006-2008 IChemE: Committee Member, Computer-Aided

45

Process Engineering Group EPSRC: Member of Peer Review College Co-chair, Foundations of Molecular Modeling and Simulations 2015 (FOMMS 2015), Oregon

Reviewer for AIChE Journal, Chemical Engineering Research and Design, Computers and Chemical Engineering, Molecular Physics, Journal of Power Sources, Energy & Fuels, Journal of Global Optimization, Industrial and Engineering Chemistry Research, Fluid Phase Equilibria, Chemical Engineering Science, Computers and Chemical Engineering, Imperial College Press, Mathematical Programming, Optimization and Engineering.

Academic Collaborations Argonne National Laboratory, UCL, University of Manchester, University of Edinburgh, University of Cardiff, University of Paderborn, University of Pannonia, ETH Zürich, National Technical University of Athens, Centre for Research and Technology-Hellas, University of Notre-Dame.

Industrial Collaborations BP, CaO Hellas, Dynamic Extraction, Julius Montz, Novartis, Pfizer, Process Design Center, Procter & Gamble, Process Systems Enterprise, Public Power Corporation, Scottish Power, Syngenta

PublicationsJournal Articles1. Burger J, Papaioannou V, Gopinath S, Jackson G, Galindo A,

Adjiman CS, 2015, A hierarchical method to integrated solvent and process design of physical CO2 absorption using the SAFT- Mie approach, AICHE JOURNAL, Vol: 61, Pages: 3249-3269, ISSN: 0001-1541

2. Habgood M, Sugden IJ, Kazantsev AV, Adjiman CS, Pantelides CC, 2015, Efficient Handling of Molecular Flexibility in Ab Initio Generation of Crystal Structures, JOURNAL OF CHEMICAL THEORY AND COMPUTATION, Vol: 11, Pages: 1957-1969, ISSN: 1549-9618

3. Kleniati P-M, Adjiman CS, 2015, A generalization of the Branch-and-Sandwich algorithm: From continuous to mixed-integer nonlinear bilevel problems, COMPUTERS & CHEMICAL ENGINEERING, Vol: 72, Pages: 373-386, ISSN: 0098-1354

4. Nerantzis D, Adjiman CS, 2015, Deterministic Global Optimization and Transition States, 12TH INTERNATIONAL SYMPOSIUM ON PROCESS SYSTEMS ENGINEERING (PSE) AND 25th EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING (ESCAPE), PT A, Vol: 37, Pages: 851-856, ISSN: 1570-7946

5. Papadokonstantakis S, Badr S, Hungerbühler K, Papadopoulos AI, Damartzis T, Seferlis P, Forte E, Chremos A, Galindo A, Jackson G, Adjiman C, 2015, Toward Sustainable Solvent-Based Postcombustion CO2 Capture: From Molecules to Conceptual Flowsheet Design, Computer Aided Chemical Engineering, Vol: 36, Pages: 279-310, ISSN: 1570-7946

6. Papaioannou V, Calado F, Lafitte T, Dufal S, Sadeqzadeh M, Jackson G, Adjiman CS, Galindo A, 2015, Application of the SAFT-γ Mie group contribution equation of state to fluids of

relevance to the oil and gas industry, Fluid Phase Equilibria, ISSN: 0378-3812

7. Rhazaoui K, Cai Q, Kishimoto M, Tariq F, Somalu MR, Adjiman CS, Brandon NP, 2015, Towards the 3D Modelling of the Effective Conductivity of Solid Oxide Fuel Cell Electrodes – Validation against experimental measurements and prediction of electrochemical performance, ELECTROCHIMICA ACTA, Vol: 168, Pages: 139-147, ISSN: 0013-4686

8. Adjiman CS, Galindo A, Jackson G, 2014, Molecules Matter: The Expanding Envelope of Process Design, PROCEEDINGS OF THE 8th INTERNATIONAL CONFERENCE ON FOUNDATIONS OF COMPUTER-AIDED PROCESS DESIGN, Vol: 34, Pages: 55-64, ISSN: 1570-7946

9. Cai Q, Adjiman CS, Brandon NP, 2014, Optimal control strategies for hydrogen production when coupling solid oxide electrolysers with intermittent renewable energies, JOURNAL OF POWER SOURCES, Vol: 268, Pages: 212-224, ISSN: 0378-7753

10. Dufal S, Papaioannou V, Sadeqzadeh M, Pogiatzis T, Chremos A, Adjiman CS, Jackson G, Galindo A, 2014, Prediction of Thermodynamic Properties and Phase Behavior of Fluids and Mixtures with the SAFT-gamma Mie Group-Contribution Equation of State, JOURNAL OF CHEMICAL AND ENGINEERING DATA, Vol: 59, Pages: 3272-3288, ISSN: 0021-9568

11. Jackson G, Galindo A, Adjiman CS, Müller EA, 2014, Employing a SAFT equation of state to obtain force fields for use in coarse-grained molecular simulations, Pages: 1231-1232

12. Kleniati P-M, Adjiman CS, 2014, Branch-and-Sandwich: a deterministic global optimization algorithm for optimistic bilevel programming problems. Part I: Theoretical development, JOURNAL OF GLOBAL OPTIMIZATION, Vol: 60, Pages: 425-458, ISSN: 0925-5001

13. Kleniati P-M, Adjiman CS, 2014, Branch-and-Sandwich: a deterministic global optimization algorithm for optimistic bilevel programming problems. Part II: Convergence analysis and numerical results, JOURNAL OF GLOBAL OPTIMIZATION, Vol: 60, Pages: 459-481, ISSN: 0925-5001

14. Pantelides CC, Adjiman CS, Kazantsev AV, 2014, General Computational Algorithms for Ab Initio Crystal Structure Prediction for Organic Molecules, PREDICTION AND CALCULATION OF CRYSTAL STRUCTURES: METHODS AND APPLICATIONS, Vol: 345, Pages: 25-58, ISSN: 0340-1022

15. Papadopoulos AI, Badr S, Chremos A, Forte E, Zarogiannis T, Seferlis P, Papadokonstantakis S, Adjiman CS, Galindo A, Jackson G, 2014, Efficient screening and selection of post-combustion CO2 capture solvents, Chemical Engineering Transactions, Vol: 39, Pages: 211-216, ISSN: 2283-9216

16. Papadopoulos AI, Badr S, Chremos A, Forte E, Zarogiannis T, Seferlis P, Papadokonstantakis S, Adjiman CS, Galindo A, Jackson G, 2014, Molecular design of optimum CO2 capture solvents: From conceptual screening to SAFT-based validation, Pages: 382-383

17. Pereira FE, Galindo A, Jackson G, Adjiman C, 2014, On the impact of using volume as an independent variable for the solution of P-T fluid-phase equilibrium with equations of state, COMPUTERS & CHEMICAL ENGINEERING, Vol: 71, Pages: 67-76, ISSN: 0098-1354

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18. Rhazaoui K, Cai Q, Adjiman CS, Brandon NP, 2014, Towards the 3D modeling of the effective conductivity of solid oxide fuel cell electrodes – II. Computational parameters, CHEMICAL ENGINEERING SCIENCE, Vol: 116, Pages: 781-792, ISSN: 0009-2509

19. Schreckenberg JMA, Dufal S, Haslam AJ, Adjiman CS, Jackson G, Galindo A, 2014, Modelling of the thermodynamic and solvation properties of electrolyte solutions with the statistical associating fluid theory for potentials of variable range, MOLECULAR PHYSICS, Vol: 112, Pages: 2339-2364, ISSN: 0026-8976

20. Siougkrou E, Galindo A, Adjiman CS, 2014, On the optimal design of gas-expanded liquids based on process performance, CHEMICAL ENGINEERING SCIENCE, Vol: 115, Pages: 19-30, ISSN: 0009-2509

21. Vasileiadis M, Pantelides CC, Adjiman CS, 2014, Prediction of the crystal structures of axitinib, a polymorphic pharmaceutical molecule, Chemical Engineering Science, Vol: 121, Pages: 60-76, ISSN: 0009-2509

Selected Refereed Conference Publications 1. Kazazakis N, Adjiman CS, 2014, GLOBIE: An algorithm for the

deterministic global optimization of box-constrained NLPs, PROCEEDINGS OF THE 8th INTERNATIONAL CONFERENCE ON FOUNDATIONS OF COMPUTER-AIDED PROCESS DESIGN, Vol: 34, Pages: 669-674, ISSN: 1570-7946

2. Papaioannou V, Lafitte T, Avendano C, Adjiman CS, Jackson G, Müller EA, Galindo A, 2014, Group contribution methodology based on the statistical associating fluid theory for heteronuclear molecules formed from Mie segments, JOURNAL OF CHEMICAL PHYSICS, Vol: 140, ISSN: 0021-9606

I David L. Bogle CEng FREng FIChemE

Professor of Chemical Engineering, Department of Chemical Engineering, University College London QualificationsPhD in Chemical Engineering (Imperial College London) MSc in Chemical Engineering (Imperial College London) DIC in Engineering (Imperial College London) BEng with honours in Chemical Engineering (Imperial College London)

Awards and DistinctionsFellow of the Royal Academy of Engineering (2005) Fellow of Institution of Chemical Engineers (1997) IChemE Council Medal (2005)

Research InterestsNumerical global optimisation techniques for process design. Controllability analysis of nonlinear systems. Process modelling of pressure swing adsorption and desalination units. Systems Biology and Systems Medicine with particular focus on liver physiology and protein networks in cancer.

Other ActivitiesPro-Vice-Provost, Head of the UCL Doctoral School Member of College of Engineering for the Engineering & Physical Sciences Research Council (EPSRC) Vice Chair of BBSRC Multidisciplinary Synthetic Biology Research Centres panel (2014) Vice Chair of EPSRC Engineering Fellowships for Growth – Synthetic Biology panel (2014) Committee member of Computer Aided Process Engineering Subject Group of Institution of Chemical Engineers Member of European Federation of Chemical Engineers Working Party on Computer Aided Process Engineering (UK representative) Member of International Federation of Automatic Control (IFAC) Technical Committee on Control of Environmental Systems Member of Royal Academy International CommitteeChair Royal Academy of Engineering Distinguished Visiting Fellowship Scheme Chair Royal Academy of Engineering Industry Academic Partnerships Programme Steering Group (from 2016) Chair League of European Research Universities Doctoral Studies Community UK representative on European Research Area Steering Group on Human Resources and Mobility Working Group on Doctoral Education Advisory Board of University of Zurich Graduate Campus Advisory Board AICES (Aachen Institute for Computational Engineering Science) RWTH Aachen

Reviewer forEPSRC, BBSRC, Royal Academy of Engineering, Royal Society, Industrial and Engineering Chemistry Research, Computers and Chemical Engineering, AIChEJournal, Engineering in the Life Sciences, Hepatology, Fonds National de la Recherche Luxembourg, Polish Research Council.

Academic CollaborationsUCL Chemical Engineering, Centre for Mathematics and Physics in the Life Sciences and Experimental Biology (UCL), UCL Hepatology, UCL Cancer Institute, University of Palermo.

Industrial CollaborationsPricewaterhouseCoopers

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PublicationsJournal Articles1. Perez-Galvan, C., & Bogle, I. D. L. (2014). Comparison

between Interval Methods to Solve Initial Value Problems in Chemical Process Design. 24th EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING, PTS A AND B, 33, 1405-1410.

2. Al-Fulaij, H., Cipollina, A., Micale, G., Ettouney, H., & Bogle, D. (2014). Eulerian-Eulerian modelling and computational fluid dynamics simulation of wire mesh demisters in MSF plants. ENGINEERING COMPUTATIONS, 31 (7), 1242-1260. doi:10.1108/EC-03-2012-0063

3. Alsoudani, T. M., & Bogle, I. D. L. (2014). From discretization to regularization of composite discontinuous functions. Computers & Chemical Engineering, 62, 139-160. doi:10.1016/j.compchemeng.2013.11.019

4. Tedesco M., Mazzola P., Micale G., Bogle I.D.L., Papapetrou, Tamburini A., Cipollina A. (2014) Reverse Electrodialysis Process: Analysis of Optimal Conditions for Process Scale-up. In Proc EDS Conference on “Desalination for the Environment, Clean Water and Energy”, Cyprus, May 2014.

5. Perez-Galvan, C. and Bogle, I. D. L. Deterministic Global Dynamic Optimisation using Interval Analysis (2014) in Proc 12th International Conference on Process Systems Engineering, Copenhagen, 791-796

6. Tedesco M., Cipollina A., Tamburini A., Bogle I.D.L., and MICALE G. (2015) Reverse electrodialysis process with seawater and concentrated brines: a comprehensive model for equipment design. Chemical Engineering Research and Design 93 441-456

7. Mendes M.F. and Bogle I.D.L. (2015) Evaluation of the effects and mechanisms of bioactive components present in hypoglycemic plants. Int.J. Chem. & Biomolec. Sci. 1/3 167-178

Nigel Brandon OBE FREng

Director of the Sustainable Gas Institute (SGI), Department of Earth Science & Engineering, Imperial College London

Qualifications PhD in Electrochemical Engineering (Imperial College London) BSc (Eng) in Minerals Technology (Imperial College London)

Awards and Distinctions 2014 Francis Bacon Medal, American Society of Mechanical Engineers2014 RISE (Recognising Inspirational Scientists and Engineers) Fellow2014 Co-Director, Energy SuperStore2014 Director Sustainable Gas Institute2013 Member of Council, Royal Academy of Engineering2012 Director Hydrogen and Fuel Cells Supergen Hub 2012 Director Energy Storage Research Network2012 BRE Fellow 2012 Visiting Professor, Energy Research Institute, NTU Singapore 2011 Baker Medal, Institute of Civil Engineering2011 OBE for services to UK-China science 2008 Fellow of the Royal Academy of Engineering 2008 Fellow of the City and Guilds of London Institute2007 Royal Academy of Engineering Silver Medal2006 Chartered Engineer2006 Fellow of the Institute of Materials, Minerals and Mining2006 Fellow of the Energy Institute2006 Inaugural Energy Senior Research Fellow to the Research

Councils Energy programme

Research InterestsProfessor Brandon’s research is focused on electrochemical power sources for fuel cell and energy storage applications. He collaborates extensively with industry in this field, as well with other research centres and universities around the world, and he is Director of the RC Energy programme funded Hydrogen and Fuel Cells SUPERGEN Hub (www.h2fcsupergen.com). He was the founding Director of the Energy Futures Lab at Imperial College (www.imperial.ac.uk/energyfutureslab), and a founder of Ceres Power (www.cerespower.com), an AIM listed fuel cell company spun out from Imperial College. In 2014 he was appointed to the BG Chair in Sustainable Gas and as Director of the Sustainable Gas Institute at Imperial College.

PublicationsJournal Articles1. Bahadori L, Chakrabarti MH, Hashim MA, Manan NSA, Mjalli

FS, AlNashef IM, Brandon NP, 2015, Temperature Effects on the Kinetics of Ferrocene and Cobaltocenium in Methyltriphenylphosphonium Bromide Based Deep Eutectic Solvents, JOURNAL OF THE ELECTROCHEMICAL SOCIETY, Vol: 162, Pages: H617-H624, ISSN: 0013-4651

2. Bahadori L, Chakrabarti MH, Manan NSA, Hashim MA, Mjalli FS, AlNashef IM, Brandon N, 2015, The Effect of Temperature on Kinetics and Diffusion Coefficients of Metallocene Derivatives in Polyol-Based Deep Eutectic Solvents, PLOS ONE, Vol: 10, ISSN: 1932-6203

3. Boldrin P, Millan-Agorio M, Brandon NP, 2015, Effect of Sulfur- and Tar-Contaminated Syngas on Solid Oxide Fuel Cell Anode Materials, ENERGY & FUELS, Vol: 29, Pages: 442-446, ISSN: 0887-0624 Boldrin P, Ruiz-Trejo E, Yu J, Gruar RI, Tighe CJ, Chang K-C, Ilavsky J, Darr JA, Brandon N, 2015, Nanoparticle scaffolds for syngas-fed solid oxide fuel cells, JOURNAL OF MATERIALS CHEMISTRY A, Vol: 3, Pages: 3011-3018, ISSN: 2050-7488

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4. Chakrabarti MH, Manan NSA, Brandon NP, Maher RC, Mjalli FS, AlNashef IM, Hajimolana SA, Hashim MA, Hussain MA, Nir D, 2015, One-pot electrochemical gram-scale synthesis of graphene using deep eutectic solvents and acetonitrile, CHEMICAL ENGINEERING JOURNAL, Vol: 274, Pages: 213-223, ISSN: 1385-8947

5. Dewage HH, Wu B, Tsoi A, Yufit V, Offer G, Brandon N, 2015, A novel regenerative hydrogen cerium fuel cell for energy storage applications, JOURNAL OF MATERIALS CHEMISTRY A, Vol: 3, Pages: 9446-9450, ISSN: 2050-7488

6. Duboviks V, Lomberg M, Maher RC, Cohen LF, Brandon NP, Offer GJ, 2015, Carbon deposition behaviour in metal-infiltrated gadolinia doped ceria electrodes for simulated biogas upgrading in solid oxide electrolysis cells, JOURNAL OF POWER SOURCES, Vol: 293, Pages: 912-921, ISSN: 0378-7753

7. Mazur C, Contestabile M, Offer GJ, Brandon NP, 2015, Understanding the drivers of fleet emission reduction activities of the German car manufacturers, Environmental Innovation and Societal Transitions, Vol: 16, Pages: 3-21

8. Parkes MA, Refson K, d’Ayezac M, Offer GJ, Brandon NP, Harrison NM, 2015, Chemical Descriptors of Yttria-Stabilized Zirconia at Low Defect Concentration: An ab Initio Study, JOURNAL OF PHYSICAL CHEMISTRY A, Vol: 119, Pages: 6412-6420, ISSN: 1089-5639

9. Rhazaoui K, Cai Q, Kishimoto M, Tariq F, Somalu MR, Adjiman CS, Brandon NP, 2015, Towards the 3D Modelling of the Effective Conductivity of Solid Oxide Fuel Cell Electrodes – Validation against experimental measurements and prediction of electrochemical performance, ELECTROCHIMICA ACTA, Vol: 168, Pages: 139-147, ISSN: 0013-4686

10. Ruiz-Trejo E, Atkinson A, Brandon NP, 2015, Metallizing porous scaffolds as an alternative fabrication method for solid oxide fuel cell anodes, JOURNAL OF POWER SOURCES, Vol: 280, Pages: 81-89, ISSN: 0378-7753

11. Ruiz-Trejo E, Zhou Y, Brandon NP, 2015, On the manufacture of silver-BaCe0.5Zr0.3Y0.16Zn0.04O3-delta composites for hydrogen separation membranes, INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, Vol: 40, Pages: 4146-4153, ISSN: 0360-3199

12. Stockford C, Brandon N, Irvine J, Mays T, Metcalfe I, Book D, Ekins P, Kucernak A, Molkou V, Steinberger-Wilckens R, Shah N, Dodds P, Dueso C, Samsatli S, Thompson C, 2015, H2FC SUPERGEN: An overview of the Hydrogen and Fuel Cell research across the UK, INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, Vol: 40, Pages: 5534-5543, ISSN: 0360-3199

13. Teng F, Pudjianto D, Strbac G, Brandon N, Thomson A, Miles J, 2015, Potential value of energy storage in the UK electricity system, PROCEEDINGS OF THE INSTITUTION OF CIVIL ENGINEERS-ENERGY, Vol: 168, Pages: 107-117, ISSN: 1751-4223

14. Tonekabonimoghadam S, Akikur RK, Hussain MA, Hajimolana S, Saidur R, Ping HW, Chakrabarti MH, Brandon NP, Aravind PV, Nayagar JNS, Hashim MA, 2015, Mathematical modelling and experimental validation of an anode-supported tubular solid oxide fuel cell for heat and power generation, ENERGY, Vol: 90, Pages: 1759-1768, ISSN: 0360-5442

15. Wu B, Yufit V, Merla Y, Martinez-Botas RF, Brandon NP, Offer GJ, 2015, Differential thermal voltammetry for tracking of degradation in lithium-ion batteries, JOURNAL OF POWER SOURCES, Vol: 273, Pages: 495-501, ISSN: 0378-7753

16. Cai Q, Adjiman CS, Brandon NP, 2014, Optimal control strategies for hydrogen production when coupling solid oxide electrolysers with intermittent renewable energies, JOURNAL OF POWER SOURCES, Vol: 268, Pages: 212-224, ISSN: 0378-7753

17. Chakrabarti MH, Brandon NP, Hajimolana SA, Tariq E, Yufit V, Hashim MA, Hussain MA, Low CTJ, Aravind PV, 2014, Application of carbon materials in redox flow batteries, JOURNAL OF POWER SOURCES, Vol: 253, Pages: 150-166, ISSN: 0378-7753

18. Chung D-W, Shearing PR, Brandon NP, Harris SJ, Garcia RE, 2014, Particle Size Polydispersity in Li-Ion Batteries, JOURNAL OF THE ELECTROCHEMICAL SOCIETY, Vol: 161, Pages: A422-A430, ISSN: 0013-4651

19. Cooper SJ, Eastwood DS, Gelb J, Damblanc G, Brett DJL, Bradley RS, Withers PJ, Lee PD, Marquis AJ, Brandon NP, Shearing PR, 2014, Image based modelling of microstructural heterogeneity in LiFePO4 electrodes for Li-ion batteries, JOURNAL OF POWER SOURCES, Vol: 247, Pages: 1033-1039, ISSN: 0378-7753

20. Duboviks V, Maher RC, Kishimoto M, Cohen LF, Brandon NP, Offer GJ, 2014, A Raman spectroscopic study of the carbon deposition mechanism on Ni/CGO electrodes during CO/CO2 electrolysis, PHYSICAL CHEMISTRY CHEMICAL PHYSICS, Vol: 16, Pages: 13063-13068, ISSN: 1463-9076

21. Eastwood DS, Bradley RS, Tariq F, Cooper SJ, Taiwo OO, Gelb J, Merkle A, Brett DJL, Brandon NP, Withers PJ, Lee PD, Shearing PR, 2014, The application of phase contrast X-ray techniques for imaging Li-ion battery electrodes, NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION B-BEAM INTERACTIONS WITH MATERIALS AND ATOMS, Vol: 324, Pages: 118-123, ISSN: 0168-583X

22. Eastwood DS, Yufit V, Gelb J, Gu A, Bradley RS, Harris SJ, Brett DJL, Brandon NP, Lee PD, Withers PJ, Shearing PR, 2014, Lithiation- Induced Dilation Mapping in a Lithium- Ion Battery Electrode by 3D X- Ray Microscopy and Digital Volume Correlation, ADVANCED ENERGY MATERIALS, Vol: 4, ISSN: 1614-6832

23. Guerra C, Lanzini A, Leone P, Santarelli M, Brandon NP, 2014, Optimization of dry reforming of methane over Ni/YSZ anodes for solid oxide fuel cells, JOURNAL OF POWER SOURCES, Vol: 245, Pages: 154-163, ISSN: 0378-7753

24. Howey DA, Mitcheson PD, Yufit V, Offer GJ, Brandon NP, 2014, Online Measurement of Battery Impedance Using Motor Controller Excitation, IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, Vol: 63, Pages: 2557-2566, ISSN: 0018-9545

25. Kalyvas C, Kucernak A, Brett D, Hinds G, Atkins S, Brandon N, 2014, Spatially resolved diagnostic methods for polymer electrolyte fuel cells: a review, WILEY INTERDISCIPLINARY REVIEWS-ENERGY AND ENVIRONMENT, Vol: 3, Pages: 254-275, ISSN: 2041-8396

26. Kishimoto M, Lomberg M, Ruiz-Trejo E, Brandon NP, 2014, Enhanced triple-phase boundary density in infiltrated electrodes for solid oxide fuel cells demonstrated by high-

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resolution tomography, JOURNAL OF POWER SOURCES, Vol: 266, Pages: 291-295, ISSN: 0378-7753

27. Lomberg M, Ruiz-Trejo E, Offer G, Brandon NP, 2014, Characterization of Ni-Infiltrated GDC Electrodes for Solid Oxide Cell Applications, JOURNAL OF THE ELECTROCHEMICAL SOCIETY, Vol: 161, Pages: F899-F905, ISSN: 0013-4651

28. Rhazaoui K, Cai Q, Adjiman CS, Brandon NP, 2014, Towards the 3D modeling of the effective conductivity of solid oxide fuel cell electrodes – II. Computational parameters, CHEMICAL ENGINEERING SCIENCE, Vol: 116, Pages: 781-792, ISSN: 0009-2509

29. Ruiz-Trejo E, Boldrin P, Lubin A, Tariq F, Fearn S, Chater R, Cook SN, Atkinson A, Gruar RI, Tighe CJ, Darr J, Brandon NP, 2014, Novel Composite Cermet for Low-Metal-Content Oxygen Separation Membranes, CHEMISTRY OF MATERIALS, Vol: 26, Pages: 3887-3895, ISSN: 0897-4756

30. Tariq F, Kishimoto M, Yufit V, Cui G, Somalu M, Brandon NP, 2014, 3D imaging and quantification of interfaces in SOFC anodes, JOURNAL OF THE EUROPEAN CERAMIC SOCIETY, Vol: 34, Pages: 3755-3761, ISSN: 0955-2219

31. Tariq F, Yufit V, Eastwood DS, Merla Y, Biton M, Wu B, Chen Z, Freedman K, Offer G, Peled E, Lee PD, Golodnitsky D, Brandon N, 2014, In-Operando X-ray Tomography Study of Lithiation Induced Delamination of Si Based Anodes for Lithium-Ion Batteries, ECS ELECTROCHEMISTRY LETTERS, Vol: 3, Pages: A76-A78, ISSN: 2162-8726

32. Tariq F, Yufit V, Kishimoto M, Shearing PR, Menkin S, Golodnitsky D, Gelb J, Peled E, Brandon NP, 2014, Three-dimensional high resolution X-ray imaging and quantification of lithium ion battery mesocarbon microbead anodes, JOURNAL OF POWER SOURCES, Vol: 248, Pages: 1014-1020, ISSN: 0378-7753

33. Troxler Y, Wu B, Marinescu M, Yufit V, Patel Y, Marquis AJ, Brandon NP, Offer GJ, 2014, The effect of thermal gradients on the performance of lithium-ion batteries, JOURNAL OF POWER SOURCES, Vol: 247, Pages: 1018-1025, ISSN: 0378-7753

34. Wu B, Parkes MA, Yufit V, De Benedetti L, Veismann S, Wirsching C, Vesper F, Martinez-Botas RF, Marquis AJ, Offer GJ, Brandon NP, 2014, Design and testing of a 9.5 kWe proton exchange membrane fuel cell-supercapacitor passive hybrid system, INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, Vol: 39, Pages: 7885-7896, ISSN: 0360-3199

35. Yang W, Zhao Y, Liso V, Brandon N, 2014, Optimal design and operation of a syngas-fuelled SOFC micro-CHP system for residential applications in different climate zones in China, ENERGY AND BUILDINGS, Vol: 80, Pages: 613-622, ISSN: 0378-7788

Conference Papers1. Boldrin P, Ruiz-Trejo E, Tighe C, Chang KC, Darr J, Brandon

NP, 2015, Impregnation of nanoparticle scaffolds for syngas-fed solid oxide fuel cell anodes, Pages: 1219-1227, ISSN: 1938-5862

2. Lomberg M, Boldrin P, Tariq F, Offer G, Wu B, Brandon NP, 2015, Additive manufacturing for solid oxide cell electrode fabrication, Pages: 2119-2127, ISSN: 1938-5862

3. Tariq F, Yufit V, Kishimoto M, Cui G, Somalu M, Brandon N, 2014, Advanced 3D Imaging and Analysis of SOFC Electrodes, Symposium on Solid State Ionic Devices 10 held during the 226th Meeting of the Electrochemical-Society, Publisher: ELECTROCHEMICAL SOC INC, Pages: 81-86, ISSN: 1938-5862

4. Kishimoto M, Lomberg M, Ruiz-Trejo E, Brandon NP, 2014, Towards the Microstructural Optimization of SOFC Electrodes Using Nano Particle Infiltration, Symposium on Solid State Ionic Devices 10 held during the 226th Meeting of the Electrochemical-Society, Publisher: ELECTROCHEMICAL SOC INC, Pages: 93-102, ISSN: 1938-5862

5. Maskell WC, Brett DJL, Brandon NP, 2014, Thick-film amperometric zirconia oxygen sensors: influence of cobalt oxide as a sintering aid, Publisher: IOP PUBLISHING LTD, ISSN: 0957-0233

6. Philbin SP, Jones D, Brandon NP, Hawkes AD, 2014, Exploring Research Institutes: Structures, Functioning and Typology, Portland International Conference on Management of Engineering & Technology (PICMET), Publisher: IEEE, Pages: 2569-2582, ISSN: 2159-5100

Invited Lectures1. The Role of Shale Gas in UK Energy Security, Invited lecture,

Shale Gas Environmental Summit, London, Oct 26-27th, 2015. 2. Natural Gas in the UK – a stepping stone or an end point?

Invited lecture, BIEE Gas Seminar, London, 15th October 2015.3. Electrochemistry in energy applications: policy drivers,

commercial opportunities and research challenges, Conference plenary lecture, ECS conference on electrochemical energy conversion and storage, Glasgow, 26th to 31st July 2015.

4. Visualisation and quantification of microstructural change in battery electrodes, Invited lecture, ECS conference on electrochemical energy conversion and storage, Glasgow, 26th to 31st July 2015.

5. Application of 3D imaging to design better electrodes for fuel cells and flow cells, Invited lecture, Annual meeting of the STFC Global chellenge network in batteries and electrochemical devices, Oxford, 30th June to 1st July 2015.

6. An overview of the UK Energy Storage Research Network and the Supergen Energy Storage Hub, Invited lecture, 2nd symposium on Heat and Electricity Storage, PSI, Villigen, Switzerland, 5th May 2015.

7. Correlating Solid Oxide Cell Microstructure and Performance, Invited lecture, Manufacturing Green Fuels from Renewable Energy, DTU Riso, Denmark, 15th April 2015.

8. Making Gas Greener, Invited lecture, Flame, Amsterdam, 14th April 2015.

9. Overview of energy storage technologies and options, Invited lecture, UK energy storage: The Opportunities, Renewable Energy Association, London, 12th March 2015.

10. The role of fuel cells and energy storage in low carbon energy systems, Invited lecture, Midlands Energy Consortium, Nottingham, 11th March 2015.

11. Materials Engineering for Solid Oxide Fuel Cells and Electrolysers, Invited lecture, 9th International Symposium on Hydrogen and Energy, Emmetten, Switzerland, 25-30th January 2015.

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12. Understanding electrodes in fuel cells and batteries, Invited lecture, University of Calgary, Canada, 20th November 2014.

13. The role and value of fuel cells and energy storage in low carbon energy systems, Zandmer Distinguished lecture, University of Calgary, Canada, 19th November 2014.

14. Solid Oxide Fuel Cell Electrodes – a design led approach, Invited lecture, Workshop on industrial and academic advances in Solid Oxide Fuel Cells, Imperial College, London, October 30th 2014.

15. UK Hydrogen and Fuel Cell Research – an overview, Plenary lecture, 14th International Symposium on Metal-Hydrogen Systems, Salford, Manchester, 20-25th July 2014.

16. An overview of UK Fuel Cell Research, UK-Korea workshop on fuel cells, Seoul, South Korea, 17-18th July 2014.

17. Solid Oxide Fuel Cells – from concept to commercialisation, Francis Bacon Medal award lecture, 12th ASME Fuel Cell Science, Engineering and Technology Conference, Boston, USA, June 30th to July 2nd 2014.

18. Grid scale energy storage – a transformation, Invited lecture, 3rd annual Oxford Energy Conference, Oxford, June 17th 2014.

19. Developments in Solid Oxide Fuel Cells, Invited lecture, 3rd International symposium on solid oxide fuel cells for next generation power plants: gasifier-SOFC systems, Warsaw, Poland, June 2nd 2014.

20. 3D Imaging and Analysis of SOFC Electrodes, Grove Fuel Cell Symposium, Amsterdam, 3-4th April, 2014.

21. Fuel cells for Power and Heat, Invited lecture, Innovation in Energy, Royal academy of Engineering, London, 31st March, 2014.

22. Understanding SOFC Electrodes: characterisation, design and fabrication, 10th Int Hydrogen and Fuel Cell Conference, Birmingham, 26-27 March, 2014.

23. Advances in Electrodes for Solid Oxide Fuel Cells and Electrolysers, Plenary lecture, International Conference on Nanotechnology, nanomaterials and thin films for energy applications, London, 19-21 February, 2014.

24. The Role of Renewable Energy, Invited speaker, Oxford Climate Forum,, Oxford, Feb 7-8th 2014.

25. Hydrogen – a key enabler for low carbon energy systems? Plenary lecture, Hydrogen: A vital element for our sustainable future, Bath University, Jan 30th 2014.

Benoît Chachuat

Reader in Process Systems Engineering, Department of Chemical Engineering, Imperial College London

QualificationsMEng in Environmental Engineering (1998, with Distinction – ENGEES, Strasbourg, France) MSc in Engineering Science (1998, with Distinction – Universite Louis Pasteur, Strasbourg, France) PhD in Chemical Engineering (2001, with Distinction – INPL, Nancy, France)

Awards and Distinctions (Selection)Certificate of Excellence in Reviewing, Computers & Chemical Engineering, 2013 Top-5 papers published in Journal of Global Optimization in 2013, “Convergence analysis of Taylor models and McCormick Taylor models” CAST Outstanding Young Researcher Award, AIChE, 2014CAST Directors Award, AIChE, 2015

Research Interests1. Environmental systems engineering: design and operation of wastewater treatment and recovery plants; multiscale modeling, design and operation of miroalgae culture systems. 2. Integrated membrane processes: OSN membrane cascades for separation of organic mixtures; modeling and optimization of membrane contactors; water network synthesis with membrane regenerators.3. Analysis of uncertainty propagation in dynamic systems optimization-based control and real-time optimization of dynamic systems. 4. Complete search methods and tools for global optimization and constraint satisfaction.

Other Activities (Selection) Program Coordinator (Elect.), Area 10D (Applied Mathematics and Numerical Analysis), AIChE Computing & Systems Technology (CAST) division, 2015-2016 Member of International Programming Committee, 9th IFAC Symposium on Advanced Control of Chemical Processes (ADCHEM), June 2015 UK Representative of IFAC Technical Committee on Chemical

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Process Control, since March 2015 Visiting Scientist, Department of Industrial Engineering, University of Padova, Italy (June 2014) Invited Professor, Automatic Control Laboratory, EPFL (August-September 2015)

Plenary and Keynote Lectures9th IFAC Internation Symposium on Advanced Control of Chemical Processes (ADCHEM), Plenary address, June 2015 AIChE Annual Meeting, CAST Division Plenary, November 2014

Editorial and Peer-Review ActivitiesAssociate Editor, Journal of Process Control (Elsevier) Associate Editor, Journal of Optimization Theory & Applications (Springer) Guest Editor, Optimal Control Applications & Methods (Wiley), special issue on Global and Robust Optimization of Dynamic systems Reviewer for: AIChE Journal; Annual Reviews in Control; Applied Energy; Applied Mathematics & Computations; Applied Numerical Mathematics; Automatica; Computers & Chemical Engineering; IEEE Control Systems Magazine; IEEE Transactions on Automatic Control; Industrial & Engineering Chemistry Research; Journal of Global Optimization; Journal of Optimization Theory & Applications; Journal of Process Control; Mathematical Programming; Optimization & Engineering; Optimization Letters; Optimization Methods & Software

Academic CollaborationsEPFL, Switzerland, Automatic Control Lab (Prof. Bonvin) INRIA Sophia Antipolis, France, BIOCORE Group (Dr. Bernard) INRA, France, LBE Narbonne (Dr. Steyer) MIT, Dpt Chemical Engineering (Prof. Barton) RWTH Aachen, Dpt Mechanical Engineering (Prof. Mitsos) STU Bratislava, Slovakia, Dpt Chemical Engineering (Prof. Fikar) University of Padova, Dpt Industrial Engineering (Prof. Bezzo), Dpt Biology (Prof. Morosinotto)

Industrial Collaborations Petronas, Praxair, Sydney Water, Syngenta

PublicationsJournal Articles1. J. Fu, J.M. Faust, B. Chachuat, A. Mitsos, Local Optimization

of Dynamic Programs with Guaranteed Satisfaction of Path Constraints, Automatica, 62:184-192, 2015.

2. B. Houska, M.E. Villanueva, B. Chachuat, Stable Set-Valued Integration of Nonlinear Dynamic Systems using Affine Set Parameterizations, SIAM Journal on Numerical Analysis, 53(5), 2307-2328, 2015.

3. C. Puchongkawarin, C. Menichini, C. Laso-Rubido, S.K. Fitzgerald, B. Chachuat, Model-Based Methodology for Plantwide Analysis of Wastewater Treatment Plants: Industrial Case Study, Water Practice & Technology, 10(3), 517-526, 2015.

4. A. Nikolaou, A. Bernardi, A. Meneghesso, F. Bezzo, T. Morosinotto, B. Chachuat, A Model of Chlorophyll Fluorescence in Microalgae Integrating Photoproduction, Photoinhibition and Photoregulation, Journal of Biotechnology, 194:91-99, 2015.

5. C. Puchongkawarin, C. Gomez-Mont, D.C. Stuckey, B. Chachuat, Optimization-based Methodology for the Synthesis of Wastewater Facilities for Energy and Nutrient Recovery, Chemosphere, 140:150-158, 2015.

6. M.E. Villanueva, B. Houska, B. Chachuat, Unified Framework for the Propagation of Continuous-Time Enclosures for Parametric Nonlinear ODEs, Journal of Global Optimization, 62(3):575-613, 2015.

7. C.S. Khor, B. Chachuat, N. Shah, Optimization of Water Network Synthesis: Milestones, Challenges, and Future Directions, Industrial & Engineering Chemistry Research, 53(25):10257-10275, 2014.

8. C.S. Khor, B. Chachuat, N. Shah, Fixed-Flowrate Total Water Network Synthesis under Uncertainty with Risk Management, Journal of Cleaner Production, 77:79-93, 2014.

9. B. Houska, B. Chachuat, Branch-and-Lift Algorithm for Deterministic Global Optimization in Nonlinear Optimal Control, Journal of Optimization Theory & Applications, 162(1):208-248, 2014.

Peer Reviewed International Conference Papers1. B. Chachuat, B. Houska, R. Paulen, N. Peric, J. Rajyaguru,

M.E. Villanueva, Set-Theoretic Approaches in Analysis, Estimation and Control of Nonlinear Systems (Plenary Address), International Symposium on Advanced Control of Chemical Processes (ADCHEM), 7-10 June 2015, Whistler, British Columbia, Canada.

2. J. Rajyaguru, M.E. Villanueva, B. Houska, B. Chachuat, Continuous-Time Enclosures for Uncertain Implicit Differential Equations, International Symposium on Advanced Control of Chemical Processes (ADCHEM’2015), 7-10 June 2015, Whistler, British Columbia, Canada.

3. C. Puchongkawarin, S. Fitzgerald, B. Chachuat, Plantwide Optimization of Activated Sludge Plants with Anaerobic Sludge Treatment, International Symposium on Advanced Control of Chemical Processes (ADCHEM’2015), 7-10 June 2015, Whistler, British Columbia, Canada.

4. M. Sun, B. Chachuat, E.N. Pistikopoulos, Design of Multiparametric NCO-tracking Controllers for Linear Dynamic Systems, 12th PSE and 25th ESCAPE Symposium, 31 May-4 June 2015, Copenhagen, Denmark.

5. M.E. Villanueva, J. Rajyaguru, B. Houska, B. Chachuat, Ellipsoidal Arithmetic for Nonlinear Vector-Valued Functions12th PSE and 25th ESCAPE Symposium, 31 May-4 June 2015, Copenhagen, Denmark.

6. A. Bernardi, A. Nikolaou, A. Meneghesso, B. Chachuat, T. Morosinotto, F. Bezzo, Dynamic Modelling of PI Curves in Microalgae, 12th PSE and 25th ESCAPE Symposium, 31 May-4 June 2015, Copenhagen, Denmark.

7. A. Bernardi, A. Nikolaou, A. Meneghesso, T. Morosinoto, B. Chachuat, F. Bezzo, Using Fluorescence Measurements to Model Key Phenomena in Microalgae Photosynthetic Mechanisms, 12th International Conference on Chemical and Process Engineering (ICheaP-12), 19-22 May 2015, Milano, Italy.

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8. A. Nikolaou, A. Bernardi, F. Bezzo, T. Morosinoto, B. Chachuat, A Dynamic Model of Photoproduction, Photoregulation and Photoinhibition in Microalgae using Chlorophyll Fluorescence, 19th World Congress of the International Federation of Automatic Control (IFAC’14), 24-29 Aug 2014, Cape Town, South Africa.

9. M.E. Villanueva, B. Houska, B. Chachuat, On the Stability of Set-Valued Integration for Nonlinear Parametric ODEs 24th European Symposium on Computer Aided Process Engineering (ESCAPE24),15-18 June 2014, Budapest, Hungary.

Marc Deisenroth

Lecturer in Statistical Machine Learning, Department of Computing, Imperial College London

Qualifications PhD in Computer Science (Karlsruhe Institute of Technology)

Awards and Distinctions Best Cognitive Robotics Paper Award at ICRA 2014

Research InterestsMachine Learning, Robotics, Optimization

Other Activities Area Chair at NIPS 2015

Reviewer for JMLR, NIPS, ICRA, RLDM, Cambridge University Press, AISTATS

Academic Collaborations MIT, TU Darmstadt, AIMS Senegal, Uppsala University

Book ChaptersRoberto Calandra, Nakul Gopalan, Andre Seyfarth, Jan Peters,Marc P. Deisenroth, Bayesian Gait Optimization for Bipedal Locomotion, volume 8426 (Lecture Notes in Computer Science), pp.274–290, 2014

PublicationsJournal Articles1. Marc P. Deisenroth, Dieter Fox, Carl E. Rasmussen, Gaussian

Processes for Data-Efficient Learning in Robotics and Control, IEEE Transactions on Pattern Analysis and Machine Intelligence, volume 37, pp.408–423, 2015

2. Andras Kupcsik, Marc P. Deisenroth, Jan Peters, Loh Ai Poha, Prahlad Vadakkepata, Gerhard Neumann, Model-based Contextual Policy Search for Data-Efficient Generalization of Robot Skills, Artificial Intelligence, 2015

3. Roberto Calandra, Andre Seyfarth, Jan Peters, Marc P. Deisenroth, Bayesian Optimization for Learning Gaits under Uncertainty, Annals of Mathematics and Artificial Intelligence, 2015

Conference Contributions 1. Niklas Wahlström, Thomas B. Schön, Marc P. Deisenroth,

Learning Deep Dynamical Models From Image Pixels, IFAC Symposium on System Identification, 2015

2. Roberto Calandra, Serena Ivaldi, Marc P. Deisenroth, Jan Peters, Learning Torque Control in Presence of Contacts using Tactile Sensing from Robot Skin, Proceedings of the IEEE-RAS International Conference on Humanoid Robots, 2015

3. Marc P. Deisenroth, Jun W. Ng, Distributed Gaussian Processes, Proceedings of the International Conference on Machine Learning, 2015

4. Roberto Calandra, Serena Ivaldi, Marc P. Deisenroth, Elmar Rueckert, Jan Peters, Learning Inverse Dynamics Models with Contacts, Proceedings of the IEEE International Conference on Robotics and Automation, 2015

5. Sanket Kamthe, Jan Peters, Marc P. Deisenroth, Multi-Modal Filtering for Non-linear Estimation, International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2014

6. Nooshin Haji Ghassemi, Marc P. Deisenroth, Analytic Long-Term Forecasting with Periodic Gaussian Processes, Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS), 2014

7. Roberto Calandra, Jan Peters, Andre Seyfarth, Marc P. Deisenroth, An Experimental Evaluation of Bayesian Optimization on Bipedal Locomotion, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2014

8. Marc P. Deisenroth, Peter Englert, Jan Peters, Dieter Fox, Multi-Task Policy Search for Robotics, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2014

9. Bastian Bischoff, Duy Nguyen-Tuong, Herke van Hoof, Andrew McHutchon, Carl E. Rasmussen, Alois Knoll, Jan Peters, Marc P. Deisenroth, Policy Search For Learning Robot Control Using Sparse Data, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2014

Invited Lectures and Seminars 2015 (Talks/Seminars)University of Edinburgh ETH Zurich University of Washington Sloan Summit at London Business School (Keynote) International Conference on Machine Learning (Contributed Talk) Workshop on Autonomous Citizens (Keynote) AI Society, Queen Mary University London Robotics Society, Imperial College London NIPS Workshop on Bayesian Optimization (Contributed Talk) Tesco

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2015 (Tutorials)Machine Learning Summer School (Chalmers University) Gaussian Process Winter School (University of Sheffield)

2014 (Talks/Seminars)Microsoft Research University of Sheffield TU Darmstadt University of Hertfordshire University College London Georgia Institute of Technology International Conference on Artificial Intelligence and Statistics (Contributed Talk)International Conference on Robotics and Automation (Contributed Talk) Chalmers University University of Oxford British Petroleum Workshop on Policy Learning at International Conference on Humanoid Robotics (Invited Talk)

Peter DiMaggio

Senior Lecturer, Department of Chemical Engineering, Imperial College London

Qualifications BSc in Chemical Engineering PhD in Chemical Engineering

Awards and DistinctionsRuth L. Kirschstein National Research Service Award: NIH Postdoctoral Research Fellowship, Princeton U., 2010-2012 Porter Ogden Jacobus Honorific Fellowship, Princeton U., 2008-09Kristine M. Layn Award for Outstanding Achievement in Research, Princeton U., 2007

Research Interests Holistic integration of proteomics and genomics data to understand the epigenetic basis of disease regulation Combinatorial optimisation and multivariate statistical tools for the interpretation and integration of large-scale omics datasets.

Reviewer for Analytical Chemistry, Journal of Proteome Research, Computers & Chemical Engineering, Journal of Global Optimisation, Chemical Engineering Research and Design.

Academic Collaborations MRC Clinical Sciences Centre (London), Hammersmith Hospital (London), Institut Pasteur, The Francis Crick Institute, The University of Edinburgh, Howard Hughes Medical Institute, University of Rhode Island.

Industrial Collaborations GSK AstraZeneca

Publications Journal Articles1 Horejs, C.M., Serio A., Purvis A., Gormley A.J., Bertazzo S.,

Poliniewicz A., Wang A., DiMaggio P.A., Hohenester E., Stevens M.M., “A biologically active laminin-111 fragment that modulates the epithelial-to-mesenchymal transition in embryonic stem cells”, PNAS, 111(16), 5908-5913 (2014).

2. DiMaggio P.A., O’Connor C., Shenk T., and B.A. Garcia, “Quantitative proteomic discovery of dynamic epigenome changes that control human cytomegalovirus infection”, Mol. Cell. Proteom., 13(9), 2399-410 (2014).

3. Dattani R., Gibson K., Few S., Borg A., DiMaggio P.A., Nelson J., Kazarian S., Cabral J., “Fullerene Oxidation and Clustering in Solution Induced by Light”, J Colloid Interface Sci., 446, 24-30 (2015).

4. Brownstein N.C., Guan X.,Yuan Mao Y., Zhang Q. DiMaggio P.A., Xia Q., Marshall A.G., and N.L. Young, “Paired Single Residue-Transposed Lys-N and Lys-C Digestions for Label-Free Identification of N-Terminal and C-Terminal MS/MS Peptide Product Ions: Ultrahigh Resolution FT-ICR MS and MS/MS for Peptide De Novo Sequencing”, Rapid Commun. Mass Spectrometry, 29(7), 659-66 (2015).

Invited Lectures and Seminars1. ELRIG Drug Discovery Meeting, September 2015, Telford UK. 2. Wellcome Trust Epigenomics of Common Diseases,

November 2015, Wellcome Trust Genome Campus, Cambridge, UK.

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Vivek Dua

Senior Lecturer and Departmental Tutor, Department of Chemical Engineering, UCL

Qualifications PhD in Chemical Engineering, Imperial College LondonMTech in Chemical Engineering, Indian Institute of Technology, Kanpur BE (Honours) in Chemical Engineering, Panjab University, Chandigarh

Research Interests Model Reduction, Parameter Estimation, Mixed-Integer Optimisation, Refinery-wide optimization, Solvent Extraction based Water Desalination, Synthetic Biology, Cystic Fibrosis

Other ActivitiesMember Synthetic Biology Network Co-editor of Process Systems Engineering book series

Reviewer for AIChE Journal, Industrial and Engineering Chemistry Research,Computers and Chemical Engineering, Journal of Global Optimization, Automatica, IEEE Transactions Neural Networks, IFAC Conferences

Publications Journal Articles1. Dua, V. (2015). Mixed integer polynomial programming.

Computers & Chemical Engineering, 72, 387-394. doi:10.1016/j.compchemeng.2014.07.020

2. Galvanin, F., Cao, E., Al-Rifai, N., Dua, V., & Gavriilidis, A. (2015). Optimal design of experiments for the identification of kinetic models of methanol oxidation over silver catalyst. Chimica Oggi/Chemistry Today, 33 (3), 51-56.

Conference Contributions 1. Galvanin, F., Cao, E., Al-Rifai, N., Gavriilidis, A., & Dua, V.

(2015). Model-based design of experiments for the identification of kinetic models in microreactor platforms. Computer Aided Chemical Engineering, 37, 323-328. doi:10.1016/B978-0-444-63578-5.50049-9

2. Bhatti, A. H., Thomas, G., & Dua, V. (2015). Design of a Gene Metabolator under Uncertainty. Computer Aided Chemical Engineering, 37, 2141-2146. doi:10.1016/B978-0-444-

63576-1.50051-0 3. Galvanin, A., Cao, E., Al-Rifai, N., Gavriilidis, A., & Dua, V.

(2015). A model-based experimental design study for the development of kinetic models of methanol oxidation on silver catalyst. Proceedings of CAPE Forum 2015, 87-93.

4. Charitopoulos, V., & Dua, V. (2015). A Unified Framework for Model-Based Multi-objective Process and Energy Optimisation under Uncertainty. Proceedings of SusTEM conference 2015

5. Bhatti, A. H., Thomas, G., & Dua, V. (2015). Model based design of a gene metabolic system using model predictive control. ChemEngDayUK 2015, Sheffield Charitopoulos, V., & Dua, V. (2015). Explicit Model Predictive Control of Hybrid Systems using Multi-parametric Mixed Integer Polynomial Programming. 17th British-French-German Conference on Optimization 2015, London

6. Mid, E. C., & Dua, V. (2015). Model predictive fault-tolerant control of process systems. ChemEngDayUK 2015, Sheffield

7. Jamili, E., & Dua, V. (2015). Modelling and Optimal Control of Non-Viral siRNA Delivery. AIChE Annual Meeting 2015, Salt Lake City

8. Dua, V., & Jamili, E. (2015). Modelling and optimal control of non-viral siRNA delivery. ChemEngDayUK 2015, Sheffield

9. Dua, V., & Owolaja, A. (2015). Parameter Estimation and Nonlinear Model Predictive Control Using Meshless Modelling Framework. AIChE Annual Meeting 2015, Salt Lake City

10. Vyas, J., & Dua, V. (2015). Process Synthesis and Design under Uncertainty: A Specific Class of MINLP Problems. 17th British-French-German Conference on Optimization 2015, London

Eric S Fraga

Professor of Process Systems Engineering, Department of Chemical Engineering, University College London

Qualifications BSc in Applied Mathematics (University of Alberta) MSc in Computer Science (University of Alberta) PhD in Computer Science (University of Waterloo)

Research Interests Professor Fraga’s interests lie at the interfaces between engineering, mathematics and computer science. He is specifically interested in the design of novel computer algorithms and mathematical

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techniques and their application to problems in process engineering. In the past, his research has concentrated on the development of methods for automated process design, or process synthesis, with the development of tools for the design of profitable, safe, environmentally benign chemical plants. These tools, including most prominently the Jacaranda system, use a variety of optimization methods and specially targeted visualization and interaction procedures to provide a system which is both powerful and easy to use.

Other activitiesEPSRC: Member of Peer Review CollegeMember of the International Editorial Board for the Journal of Industrial Biotechnology and BiorefineriesThe Information Technology and Control journalThe Journal of OptimizationRevista Scientia AlimentariaMember of Programme Committee for META’2016

Reviewer for A number of journals and funding agencies, covering the interfaces between computer science, mathematics and engineering.

Academic CollaborationsUniversitat d’Alacant, Spain; University of Edinburgh, UK; University of Essex, UK; University of Leeds, UK.

Publications Journal Articles1 J Beck, D Friedrich, S Brandani & E S Fraga (2015), Multi-

Objective Optimisation using Surrogate Models for the Design of VPSA Systems, Computers & Chemical Engineering 82:318-329, 10.1016/j.compchemeng.2015.07.009.

2. S Brown, E S Fraga, H Mahgerefteh & S Martynov (2015), A geometrically based grid refinement technique for multiphase flows, Computers & Chemical Engineering, 10.1016/j.compchemeng.2015.05.031.

3. C Wouters, E S Fraga & A James (2015), An energy integrated multi-microgrid, MILP approach for residential distributed energy system planning – A South Australian case-study, Energy 85:30-44, 10.1016/j.energy.2015.03.051.

4. A Zilinskas, E S Fraga, J Beck & A Varoneckas (2015), Visualisation of multi-objective decisions for the optimal design of a pressure swing adsorption system, Chemometrics and Intelligent Laboratory Systems 142:151-158, 10.1016/j.chemolab.2015.01.002.

5. E S Fraga, A Salhi, D Zhang & L G Papageorgiou (2015), Optimisation as a tool for gaining insight: An application to the built environment, Journal of Algorithms and Computational Technology 9:13-26. 10.1260/1748-3018.9.1.13

6. A Adam, E S Fraga & D J L Brett (2015), Options for residential building services design using fuel cell based micro-CHP and the potential for heat integration, Applied Energy 138:685-694, 10.1016/j.apenergy.2014.11.005.

Conference Contributions1. C Jones, K Armstrong & E Fraga (2015), Wider Impacts:

general discussion, Faraday Discussions, 10.1039/C5FD90081F.

2. M North, P Abrantes, E S Fraga et al. (2015), CO2 reduction reactions: general discussion, Faraday Discussions, 10.1039/C5FD00038

3. F. K Ronaszegi, D J L Brett & E S Fraga (2015), System modelling for hybrid solar hydrogen generation and solar heating configurations for domestic applications, in Sayigh, A. (Editor), Renewable Energy in the Service of Mankind Vol I, Springer, ISBN 978-3-319-17777-9, pages 123-131.

4. O Amusat, P Shearing & E S Fraga (2015), Optimal integrated energy systems design incorporating variable renewable energy sources, Proceedings of Sustainable Thermal Energy Management (SusTEM) 2015, 245–253.

5. E S Fraga & M Ng (2015), A framework for the analysis of the security of supply of utilising Carbon Dioxide as a chemical feedstock, Faraday Discussions 183:309-326, 10.1039/c5fd00038f. (Link)

6. C F Triana, E S Fraga & E Sorensen (2015), Energy assessment of different process configurations for the production of ethanol from lignocellulosic biomass, Proceedings of the 12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering, Krist V Gernaey, Jakob K Huusom and Rafiqul Gani (Editors), 2285-2290, ISBN: 978-0-444-63429-0.

7. C Wouters, E S Fraga & A James (2015), Techno-economic optimisation based approach for design and operation of a residential microgrid with energy export restrictions, Proceedings of the 12th International Symposium on Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering, Krist V Gernaey, Jakob K Huusom and Rafiqul Gani (Editors), 2357-2362, ISBN: 978-0-444-63429-0.

8. O Amusat, P Shearing & E S Fraga (2015), System design of renewable energy generation and storage alternatives for large scale continuous processes, Proceedings of the 12th International Symposium on

9. Process Systems Engineering and 25th European Symposium on Computer Aided Process Engineering, Krist V Gernaey, Jakob K Huusom and Rafiqul Gani (Editors), 2279-2284, ISBN: 978-0-444-63429-0

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Amparo Galindo

Professor of Physical Chemistry, Department of Chemical Engineering, Imperial College London

Qualifications PhD in Physical Chemistry, University of Sheffield BSc Chemistry, Universidad Complutense de Madrid (Spain)

Awards and DistinctionsImperial College Research Excellence Award as part of the Molecular Systems Engineering Team for high academic achievement and significant future potential (2009) Imperial College Award for Excellence in Research Supervision for an exemplary activity in inspiring and supporting research students (2007) Imperial College Award for Excellence in Teaching for outstanding contribution to undergraduate teaching (2007) ExxonMobil Teaching Fellow (2005-2009), ExxonMobil – Royal Academy of Engineering, 2005

Research InterestsMy research interests are two-fold: the development of statistical mechanical approaches for complex systems, and their application to processes relevant to industry. The tools of statistical mechanics and computer simulations offer a privileged molecular perspective of increasingly complex systems. My interest in this field is to develop fundamental approaches to contribute to the understanding of experimental systems, with a special focus on chemical processes. The goal is to be able to predict bulk properties of complex systems. We are currently concentrating on the advancement of group contribution methodologies targeting specifically solubility prediction of organic molecules (usually active pharmaceutical ingredients) and their use for the development of coarse grained force fields for use in molecular dynamics simulations. Increasingly the use of quantum mechanics and statistical mechanics to predict reaction rate constants and guide solvent design is a major interest. The impact and exposure of this work is maximised through collaborative efforts in which the aim is to promote the transfer of the theoretical developments into tools for the design and synthesis of chemical processes and products.

Other activitiesMember of the Royal Society of Chemistry (RSC) Member of the peer review college of the Engineering and Physical Sciences Research Council (EPSRC) Member of the International Scientific Advisory Committee of the European Symposium on Applied Thermodynamics (ESAT)

Editorial Activity Journal of Chemical Engineering Data Editorial Advisory Board Molecular Physics Editorial Advisory Board

Industrial CollaborationsP&G, Petronas, Pfizer, PSE Ltd., Qatar Petroleum, Shell, Syngenta.

Publications Journal Articles1. Al Ghafri SZS, Forte E, Galindo A, Maitland GC, Trusler JPM,

2015, Experimental and Modeling Study of the Phase Behavior of (Heptane plus Carbon Dioxide plus Water) Mixtures, JOURNAL OF CHEMICAL AND ENGINEERING DATA, Vol: 60, Pages: 3670-3681, ISSN: 0021-9568

2. Burger J, Papaioannou V, Gopinath S, Jackson G, Galindo A, Adjiman C, 2015, A hierarchical method to integrated solvent and process design of physical CO2 absorption using the SAFT- Mie approach, AICHE JOURNAL, Vol: 61, Pages: 3249-3269, ISSN: 0001-1541

3. Cristino AF, Morgado P, Galindo A, Filipe EJM, Palavra AMF, Nieto de Castro CA, 2015, High-temperature vapour-liquid equilibrium for ethanol-1-propanol mixtures and modeling with SAFT-VR, FLUID PHASE EQUILIBRIA, Vol: 398, Pages: 5-9, ISSN: 0378-3812

4. Dufal S, Lafitte T, Galindo A, Jackson G, Haslam AJ, 2015, Developing intermolecular-potential models for use with the SAFT-VR Mie equation of state, AICHE JOURNAL, Vol: 61, Pages: 2891-2912, ISSN: 0001-1541

5. Dufal S, Lafitte T, Haslam AJ, Galindo A, Clark GNI, Vega C, Jackson G, 2015, The A in SAFT: developing the contribution of association to the Helmholtz free energy within a Wertheim TPT1 treatment of generic Mie fluids, MOLECULAR PHYSICS, Vol: 113, Pages: 948-984, ISSN: 0026-8976

6. Jover J, Galindo A, Jackson G, Müller EA, Haslam AJ, 2015, Fluid-fluid coexistence in an athermal colloid-polymer mixture: thermodynamic perturbation theory and continuum molecular-dynamics simulation, MOLECULAR PHYSICS, Vol: 113, Pages: 2608-2628, ISSN: 0026-8976

7. Jover JF, Müller EA, Haslam AJ, Galindo A, Jackson G, Toulhoat H, Nieto-Draghi C, 2015, Aspects of Asphaltene Aggregation Obtained from Coarse-Grained Molecular Modeling, ENERGY & FUELS, Vol: 29, Pages: 556-566, ISSN: 0887-0624

8. Papadokonstantakis S, Badr S, Hungerbühler K, Papadopoulos AI, Damartzis T, Seferlis P, Forte E, Chremos A, Galindo A, Jackson G, Adjiman C, 2015, Toward Sustainable Solvent-Based Postcombustion CO2 Capture: From Molecules to Conceptual Flowsheet Design, Computer Aided Chemical Engineering, Vol: 36, Pages: 279-310, ISSN: 1570-7946

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9. Ramrattan NS, Avendano C, Müller EA, Galindo A, 2015, A corresponding-states framework for the description of the Mie family of intermolecular potentials, MOLECULAR PHYSICS, Vol: 113, Pages: 932-947, ISSN: 0026-8976

10. Adjiman CS, Galindo A, Jackson G, 2014, Molecules Matter: The Expanding Envelope of Process Design, PROCEEDINGS OF THE 8th INTERNATIONAL CONFERENCE ON FOUNDATIONS OF COMPUTER-AIDED PROCESS DESIGN, Vol: 34, Pages: 55-64, ISSN: 1570-7946

11. Al Ghafri SZS, Forte E, Maitland GC, Rodriguez-Henriquez JJ, Trusler JPM, 2014, Experimental and Modeling Study of the Phase Behavior of (Methane + CO2 + Water) Mixtures, JOURNAL OF PHYSICAL CHEMISTRY B, Vol: 118, Pages: 14461-14478, ISSN: 1520-6106

12. Braga C, Galindo A, Müller EA, 2014, Nonequilibrium molecular dynamics simulation of diffusion at the liquid-liquid interface, JOURNAL OF CHEMICAL PHYSICS, Vol: 141, ISSN: 0021-9606

13. Dufal S, Papaioannou V, Sadeqzadeh M, Pogiatzis T, Chremos A, Adjiman CS, Jackson G, Galindo A, 2014, Prediction of Thermodynamic Properties and Phase Behavior of Fluids and Mixtures with the SAFT-gamma Mie Group-Contribution Equation of State, JOURNAL OF CHEMICAL AND ENGINEERING DATA, Vol: 59, Pages: 3272-3288, ISSN: 0021-9568

14. Galindo A, 2014, Foreword: Modeling and Simulation of Real Systems, JOURNAL OF CHEMICAL AND ENGINEERING DATA, Vol: 59, Pages: 2927-2927, ISSN: 0021-9568 Galindo A, Masters A, 2014, Thermodynamics 2013 Conference, Manchester, UK, 3-6 September 2013 FOREWORD, MOLECULAR PHYSICS, Vol: 112, Pages: 2199-2202, ISSN: 0026-8976

15. Markides CN, Solanki R, Galindo A, 2014, Working fluid selection for a two-phase thermofluidic oscillator: Effect of thermodynamic properties, APPLIED ENERGY, Vol: 124, Pages: 167-185, ISSN: 0306-2619

16. Papadopoulos AI, Badr S, Chremos A, Forte E, Zarogiannis T, Seferlis P, Papadokonstantakis S, Adjiman CS, Galindo A, Jackson G, 2014, Efficient screening and selection of post-combustion CO2 capture solvents, Chemical Engineering Transactions, Vol: 39, Pages: 211-216, ISSN: 2283-9216

17. Papaioannou V, Lafitte T, Avendano C, Adjiman CS, Jackson G, Müller EA, Galindo A, 2014, Group contribution methodology based on the statistical associating fluid theory for heteronuclear molecules formed from Mie segments, JOURNAL OF CHEMICAL PHYSICS, Vol: 140, Article number 054107, ISSN: 0021-9606

18. Pereira FE, Galindo A, Jackson G, Adjiman C, 2014, On the impact of using volume as an independent variable for the solution of P-T fluid-phase equilibrium with equations of state, COMPUTERS & CHEMICAL ENGINEERING, Vol: 71, Pages: 67-76, ISSN: 0098-1354

19. Schreckenberg JMA, Dufal S, Haslam AJ, Adjiman CS, Jackson G, Galindo A, 2014, Modelling of the thermodynamic and solvation properties of electrolyte solutions with the statistical associating fluid theory for potentials of variable range, MOLECULAR PHYSICS, Vol: 112, Pages: 2339-2364, ISSN: 0026-8976

20. Siougkrou E, Galindo A, Adjiman CS, 2014, On the optimal design of gas-expanded liquids based on process performance, CHEMICAL ENGINEERING SCIENCE, Vol: 115, Pages: 19-30, ISSN: 0009-2509

Conference contributions1. Diamanti A, Adjiman C, Galindo A, 2014, Systematic study

of the accuracy of Conventional Transition State Theory in the calculations of the kinetics of a gas-phase reaction, 248th National Meeting of the American-Chemical-Society (ACS), Publisher: AMER CHEMICAL SOC, ISSN: 0065-7727

2. Jackson G, Galindo A, Adjiman CS, Müller EA, 2014, Employing a SAFT equation of state to obtain force fields for use in coarse-grained molecular simulations, Pages: 1231-1232

Federico Galvanin

Lecturer, Department of Chemical Engineering, University College London

Qualifications BSc in Chemical Engineering, University of Padova PhD in Chemical Engineering, University of Padova

Awards and Distinctions Awarded with the 1st prize in “Process Systems Enterprise Ltd. Model-Based Innovation Prize 2014” for the paper: Galvanin, F., M. Barolo, R. Padrini, S. Casonato, F. Bezzo (2014). A model-based approach to the automatic diagnosis of Von Willebrand disease. AIChE J., 60, 1718-1727.

Research InterestsDr Galvanin’s research interests lie at the interface between mathematical modelling and experimentation. The research activity is particularly focused on the use of advanced computational tools for the development of predictive models for the characterisation of complex systems in both chemistry and physiology. He has a specific expertise in the following areas: • Design of Experiments (DoE) and statistical planning • Model-based Design of Experiments (MBDoE) for model

identification • Kinetic modelling, chemical reactor modelling• Pharmacokinetics/pharmacodynamics modeling

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• Modeling of physiological systems • Parameter Estimation

The current research activity is primarily focused on the optimal design of experiments for i) the identification of kinetic models in flow reactors; ii) the development of pharmacokinetic models for the detailed study of physiological systems (diabetes and rare coagulation diseases).

Teaching Interests Teaching activities are in the areas of process design and simulation of chemical processes. Below are the modules he is currently teaching:• CENGM01P/CENGG01P Process Systems Modelling and

Design• CENG207P Process Design Principles

He is the Deputy Departmental Admissions Tutor at UCL ChemicalEngineering.

Reviewer for Industrial & Engineering Chemistry & Research, Chemical Engineering Science, Journal of Process Control, International Journal of Adaptive Control and Signal Processing, Modelling and Biological Engineering and Computing.

Academic Collaborations University of Padova on the project: “Optimal design of experiments for the identification of physiological models of Von Willebrand Diseased” Cardiff Catalysis Institute, Liverpool University, UCL Chemical Engineering (Catalysis Hub) on the project: “Merging information from batch and continuous flow experiments for the identification of kinetic models of benzyl alcohol oxidation”

Industrial Collaborations Collaboration with Syngenta (Bracknell, UK) on the MSc project: “Bringing plant potential to life through optimisation of traveling traders’ exchanges”.

Publications Journal Articles1. Galvanin, F., Cao, E., Al-Rifai, N., Dua, V., & Gavriilidis, A.

(2015). Optimal design of experiments for the identification of kinetic models of methanol oxidation over silver catalyst. Chimica Oggi/Chemistry Today, 33 (3), 51-56.

2. Galvanin, F., Barolo, M., Padrini, R., Casonato, A., & Bezzo, F. (2014). A model-based approach to the automatic diagnosis of von Willebrand disease. AIChE Journal, 60 (5), 1718-1727. doi:10.1002/aic.14373

3. Bernardi, A., Perin, G., Sforza, E., Galvanin, F., Morosinotto, T., & Bezzo, F. (2014). An Identifiable State Model To Describe Light Intensity Influence on Microalgae Growth. Industrial & Engineering Chemistry Research, 53 (16), 6738–6749. doi:10.1021/ie500523z

4. Galvanin, F., De Luca, R., Ferrentino, G., Barolo, M., Spilimbergo, S., & Bezzo, F. (2014). Bacterial inactivation on solid food matrices through supercritical CO2: A correlative study. Journal of Food Engineering, 120, 146-157.

doi:10.1016/j.jfoodeng.2013.07.027

Conference Contributions 1. Galvanin, F., Cao, E., Al-Rifai, N., Dua, V. & Gavriilidis, A.

(2015). A model-based design of experiments approach for the identification of kinetic models of methanol oxidation on silver catalyst. In: UK Catalysis Conference 2015. Loughborough (UK).

2. De Luca, R., Galvanin, F., & Bezzo, F. (2015). A framework for a direct exploitation of available information in the online model-based redesign of experiments. In M. O. Bertran, T. Bisgaard, & F. Frauzem (Eds.), 25th European Symposium on Computer Aided Process Engineering Vol. Book of Abstracts (pp. 30-31). Copenhagen.

3. Galvanin, F., Cao, E., Al-Rifai, N., Gavriilidis, A., & Dua, V. (2015). A model-based experimental design study for the development of kinetic models of methanol oxidation on silver catalyst. Proceedings of CAPE Forum 2015, 87-93.Paderborn, Germany.

4. Galvanin, F., Cao, E., Al-Rifai, N., Gavriilidis, A., & Dua, V. (2015). Model-based design of experiments for the identification of kinetic models in microreactor platforms. Amsterdam (The Netherlands): Elsevier.

5. Galvanin, F., Monte, A., Casonato, A., Padrini, R., Barolo, M., & Bezzo, F. (2014). Towards Model-Based Diagnosis of von Willebrand Disease. In P. S. V. Jiří Jaromír Klemeš, P. Y. Liew (Eds.), 24th European Symposium on Computer Aided Process Engineering (p. 583 – 588). Elsevier. doi:10.1016/B978-0-444-63456-6.50098-3

Gonzalo Guillén Gosálbez

Reader in Process Systems Engineering, Department of Chemical Engineering, Imperial College London

Qualifications MEng in Chemical Engineering (Top Student Award, Universidad de Murcia, Murcia, Spain) PhD in Process Systems Engineering (Top Student Award, UPC, Barcelona, Spain)

Awards and Distinctions Outstanding Young Investigator Award “Juan López de Peñalver” (Spanish Royal Academy of Engineering), Oct-2012Erasmus Staff Mobility for Training (ETH Zürich), June-2012

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Fulbright Postdoctoral Fellowship (Carnegie Mellon University), Oct-2006 Top Doctoral Student Award (UPC), Dec-2005FPU Pre-doctoral Scholarship (Spanish Ministry of Education and Science-UPC), Jan-2002-Jan-2006 Top Student Award in Chemical Engineering (Spanish Ministry of Education-UMU), Jun-2001

Research Interests Dr. Guillén-Gosálbez’s research interests lie at the interface of engineering, environmental sciences and computer aided systems design. Areas of particular interest include: Sustainable engineering, Multi-objective optimisation of sustainable processes, Life cycle assessment, Eco-efficiency assessment and optimisation, Stochastic programming and multi-criteria decision-making under uncertainty.

Reviewer for Member of the Editorial Board of The Scientific World Journal.

Referee for a number of journalsAIChE Journal; Asia-Pacific Journal of Chemical Engineering; Computers & Chemical Engineering; Desalination; Environmental Science & Technology; Industrial & Engineering Chemistry Research; International Journal of Hydrogen Energy; International Journal of Information Technology & Decision Making; Journal of Cleaner Production; Journal of Environmental Management; Optimization and Engineering.

Reviewer for international funding bodiesSpanish Ministry of Science and Innovation (Spain); CONICET (Argentina); Fonds National de la Recherche (Luxemburg); National Agency for the Evaluation of Universities and Research Institutes (ANVUR) (Italy); Qatar National Research Fund (Qatar).

Academic Collaborations (leading to joint publications) Carnegie Mellon University (Pittsburgh, US): Prof. Ignacio E. Grossmann, Global Optimization. ETH Zürich (Switzerland): Prof. Stefanie Hellweg, Life Cycle Assessment.Polytechnic University of Catalonia (Barcelona, Spain): Prof. Christian Blum, Hybrid Meta-heuristics. The University of Manchester (UK): Prof. Adisa Azapagic, Sustainable Industrial Systems. Universidad de Alicante (Alicante, Spain): Prof. José Caballero, Simulation-Optimisation for Process Synthesis. Universidad de Santander (Santander, Spain): Prof. Ángel Irabien, Design of Energy Systems. Universidad Michoacana de San Nicolás de Hidalgo (Mexico): Prof. Ponce-Ortega,Sustainable Supply Chains. Universidad Nacional de Tucumán (San Miguel de Tucumán, Argentina): Prof. Fernando Daniel Mele, Biofuels Supply Chains. Universitat de Lleida (Spain): Prof. Albert Sorribas, Systems Biology. University of Oklahoma (Norman, US): Prof. Miguel Bagajewicz, Optimization under Uncertainty.

Industrial CollaborationsMesser Ibérica de Gases; REPSOL; ExxonMobil Research and Engineering Company.

Publications Book Chapters1. Guillén-Gosálbez, G., You, F. Plant Location: Supply Chain

Management. Introduction to Software for Chemical Engineers, CRC Press, 2015.

2. Reyes-Labarta, J.A., Salcedo-Díaz, R., Ruiz-Femenia, R., Guillén-Gosálbez, G., Caballero, J.A. Handling of uncertainty in life cycle inventory by correlated multivariate lognormal distributions: Application to the design of supply chain networks. Computer Aided Chemical Engineering, vol. 33, 1075-1080, 2014, Pergamon-Elsevier Science ltd (UK), ISSN: 15707946.

3. Vaskan, P., Guillén-Gosálbez, G., Sorribas, A., Alves, R., Jiménez, L.Multi-level optimization framework applied to the systematic evaluation of metabolic objective functions. Computer Aided Chemical Engineering, vol. 33, 961-966, 2014, Pergamon-Elsevier Science ltd (UK), ISSN: 15707946.

Journal Articles (“*” stands for corresponding author)1. Rojas-Torres, G., Nápoles-Rivera, F., Ponce-Ortega, J.M.,

Serna-González, M., Guillén-Gosálbez, G., Jiménez-Esteller, J. Multiobjective optimization for designing and operating more sustainable water management systems for a city in Mexico. AIChE Journal, 61(8), 2428-2446, 2015.

2. Cortés-Borda, D., Guillén-Gosálbez, G.*, Jiménez, L. Assessment of nuclear energy embodied in international trade following a world multi-regional input-output approach. Energy, 91, 91-101, 2015.

3. Galán-Martín, A., Pozo, C., Guillén-Gosálbez, G.*, Vallejo, A., Esteller, L. Multi-stage linear programming model for optimizing cropping plan decisions under the new Common Agricultural Policy. Land Use Policy, 48, 515-524, 2015.

4. Pascual-González, J., Pozo, C., Guillén-Gosálbez, G.*, Jiménez-Esteller, L. Combined use of MILP and multi-linear regression to simplify LCA studies. Computers & Chemical Engineering, 82, 34-43, 2015.

5. Cortés-Borda, D., Guillén-Gosálbez, G.*, Jiménez, L. Solar energy embodied in international trade of goods and services: A multi-regional input-output approach. Energy, 82, 578-588, 2015.

6. Pascual-González, J., Guillén-Gosálbez, G.*, Mateo-Sanz, J.M., Jiménez-Esteller, L. Statistical analysis of global environmental impact patterns using a world multi-regional input-output database. Journal of Cleaner Production, 90, 360-369, 2015.

7. Pozo, C., Miró, A., Guillén-Gosálbez, G.*, Sorribas, A., Alves, R., Jiménez, L. Gobal optimization of hybrid kinetic/FBA models via outer-approximation. Computers & Chemical Engineering, 72, 325-333, 2015.

8. Carreras, J., Boer, D., Guillén-Gosálbez, G., Cabeza, L.F., Medrano, M., Jiménez, L. Multi-objective optimization of thermal modelled cubicles considering the total cost and life cycle environmental impact. Energy and Buildings, 88, 335-346, 2015.

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9. Antipova, E., Pozo, C., Guillén-Gosálbez, G.*, Boer, D., Cabeza, L.F., Jiménez, L. On the use of filters to facilitate the post-optimal analysis of the Pareto solutions in multi-objective optimization. Computers & Chemical Engineering, 74(4), 48-58, 2015.

10. Cortés-Borda, D., Ruiz-Hernández, A., Guillén-Gosálbez, G.*, Llop, M., Guimerà, R., Sales-Pardo, M. Identifying strategies for mitigating the global warming impact of the EU-25 economy using a multi-objective input-output approach. Energy Policy, 77 (21-30), 2015.

11. Kostin, A., Guillén-Gosálbez, G.*, Jiménez, L. Dimensionality reduction applied to the simultaneous optimization of the economic and life cycle environmental performance of supply chains. Journal of Production Economics, 159, 223-232, 2015.

12. Brunet, R., Boer, D., Guillén-Gosálbez, G.*, Jiménez, L. Reducing the cost, environmental impact and energy consumption of biofuel processes through heat integration. Chemical Engineering Research and Design, 93, 203-212, 2015.

13. Vaskan, P., Guillén-Gosálbez, G.*, Turkay, M., Jiménez, L. Multiobjective optimization of utility plants under several environmental indicators using an MILP-based dimensionality reduction approach. Industrial & Engineering Chemistry Research, 53(50), 19559-19572, 2014.

14. Copado-Méndez, P.J., Guillén-Gosálbez, G.*, Jiménez, L. MILP-based decomposition algorithm for dimensionality reduction in multi-objective optimization: Application to environmental and systems biology problems Computers & Chemical Engineering, 67, 137-147, 2014.

15. Vadenbo, C., Hellweg, S., Guillén-Gosálbez, G. Multi-objective optimization of waste and resource management in industrial networks – Part I: Model description. Resources, Conservation and Recycling, 89, 41-51, 2014.

16. Antipova, E., Boer, D., Guillén-Gosálbez, G., Cabeza, L.F., Jiménez, L. Multi-objective optimization coupled with life cycle assessment for retrofitting buildings. Energy and Buildings, 82, 92-99, 2014.

17. Vadenbo, C., Guillén-Gosálbez, G., Saner, D., Hellweg, S. Multi-objective optimization of waste and resource management in industrial networks – Part II: Model application to the treatment of sewage sludge. Resources, Conservation and Recycling, 89, 52-63, 2014.

18. Sabio, N., Pozo, C., Guillén-Gosálbez, G.*, Jiménez, L., Karuppiah, R., Vasudevan, V., Sawaya, N., Farrell, J.T. Multi-objective optimization under uncertainty of the economic and life cycle environmental performance of industrial processes. AIChE Journal, 60 (6), 2098-2121, 2014.

19. Brunet, R., Guillén-Gosálbez, G. *, Jiménez, L. Minimization of the nonrenewable energy consumption in bioethanol production processes using a solar-assisted steam generation system. AIChE Journal, 60 (2), 500-506, 2014.

20. Corsano, G., Guillén-Gosálbez, G.*, Montagna, J.M. Solution strategies for the design and planning of supply chains and embedded plants. Computers & Chemical Engineering, 60, 154-171, 2014.

21. Vaskan, P., Guillén-Gosálbez, G.*, Jiménez, L. Decomposition algorithm for GIS-based MILPmodels: Application to sewage

sludge amendment. Industrial & Engineering Chemistry Research, 52 (49), 17640-17647, 2014.

22. Brunet, R., Guillén-Gosálbez, G.*, Jiménez, L. Combined simulation-optimization methodology to reduce the environmental impact of pharmaceutical processes: Application to the production of Penicillin v. Journal of Cleaner Production, 76(1), 55-63, 2014.

Conference Contributions 1. Carreras, J., Boer, D., Jiménez, Guillén-Gosálbez, G.

Combined Use of Dimensionality Reduction and Surrogate Modelling for the Multi-Objective Optimization of Buildings. AIChE Annual Meeting, Salt Lake City, US, November 2015.

2. Ewertowska, A., Galán, A., Jiménez, L., Gavaldá, J., Guillén-Gosálbez, G. Assessment of the Environmental Efficiency of the Electricity Mix of the Top European Economies Via Data Envelopment Analysis. AIChE Annual Meeting, Salt Lake City, US, November 2015.

3. Galán, A., Jiménez, L., Guillén-Gosálbez, G. Multi-Objective Optimization Applied to Sustainable Rain-Fed and Irrigated Crop Production: A Case Study of Wheat Production in Spain. AIChE Annual Meeting. Salt Lake City, US, November 2015.

4. Cortés, D., Jiménez, L., Guillén-Gosálbez, G. Multi-Objective Optimization Combined with Input-Output and Eco-Cost Assessment for Decarbonizing the European Economy. AIChE Annual Meeting. Salt Lake City, US, November 2015.

5. Tulus, V., Boer, D., Jiménez, L. Guillén-Gosálbez, G. Optimization of Thermal Energy Supply By Central Solar Heating Plants with Seasonal Storage. AIChE Annual Meeting. Salt Lake City, US, November 2015.

6. Dauda, I., Jobson, M., Guillén-Gosálbez, G. Combined with the Analytic Hierarchy Process for the Design of Chemical Processes Under Uncertainty: Application to the Synthesis of Heat Exchanger Networks. AIChE Annual Meeting. Salt Lake City, US, November 2015.

7. Copado-Méndez, P., Guillén-Gosálbez, G., Jiménez-Esteller, L. Systematic framework for reducing the number of objectives in multi-objective optimization: Application to the design of environmentally conscious supply chains. 17th British-French-German Conference on Optimization, London, UK, June 2015.

8. Guillén-Gosálbez, G., Ruíz-Femenia, Caballero, J.A., Jiménez, L. Identifying the Preferred Subset of Alternatives for Environmental Improvements Via an MILP Approach Based on the Analytic Hierarchy Process. Atalanta, US, November 2014.

9. Pascual, J., Guillén-Gosálbez, G., Jiménez, L., Mateo-Sanz. Statistical Analysis of Global Environmental Impact Patterns Using a World Multi-Regional Input Output Database. AIChE Annual Meeting. Atalanta, US, November 2014.

Invited Lectures and Seminars1. Benchmark analysis of a top British University in Chemical

Engineering, Universitat Rovira i Virgili (Tarragona, Spain), January 2015.

2. Multi-objective optimisation coupled with life cycle assessment for the development of sustainable processes, Luxembourg Institute of Science and Technology (LIST) (Luxembourg City, Luxembourg), January 2015.

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3. Systematic tools based on mathematical programming for the life cycle optimisation of sustainable processes, BASF (Ludwigshafen, Germany), June 2015. Systematic optimisation tools applied to sustainable engineering, Joint Research Centre in Ispra (Ispra, Italy), May 2015.

4. Teaching Design Project at The University of Manchester (Reading, UK), December 2014.

5. Systematic multi-criteria decision-making tools for the design and planning of more sustainable processes, Northwestern University (Evanston, US), May 2014.

Adam Hawkes

Senior Lecturer in Energy Systems, Department of Chemical Engineering, Imperial College London

Qualifications PhD in Energy Systems ModellingB.Eng (Hons)

Awards and Distinctions Baker Medal, Institution of Civil Engineers, 2011

Research InterestsAdam’s areas of research interest fall into five categories:1. Economy‐wide energy systems modelling2. Technologies and pathways for low-carbon heat3. Design and operation of microgrids and more integrated/

coordinated energy systems4. Fuel cells, polygeneration, and other cutting‐edge energy

conversion technologies5. Residential energy supply and demand, with a focus on

microgenerationIn the field of energy systems modelling, Adam’s research seeks to bridge the gap between siloed energy technology assessment and the role of those technologies in integrated energy systems. Multi-scale modelling is applied to reflect the critical design and operational parameters of energy technologies and infrastructures into the energy system as a whole, providing engineers and policy makers with insight into the value of particular technology characteristics, and aiding prioritisation of technology R&D.

Other ActivitiesMember, European Council for an Energy Efficient Economy (ECEEE), 2013–2015

Member, Energy InstituteChartered Engineer, Engineering Council UK

Reviewer for Energy, Applied Energy, Applied Thermal Engineering, Nature Climate Change, Energy Policy

Academic Collaborations Collaborator, IEA ECBCS Annex 54 on Residential MicrogenerationCollaborator, IEA Annex 42 on Residential CogenerationResearcher, UKERC Microgeneration Theme

Industrial CollaborationsCeres Power Ltd, Techno Economic Modelling of Solid Oxide Fuel CellsEDF, Techno Economic Modelling of Micro‐CHP Systems

PublicationsReports1. Gross R, Speirs J, Hawkes AD, Skillings S, Heptonstall P,

2014, Could retaining old coal lead to a policy own goal?2. McDowall W, Francis L, Staffell I, Grünewald P, Kansara T,

Ekins P, Dodds P, Hawkes AD, Agnolucci Petal., 2014, The role of fuel cells and hydrogen in providing affordable, secure and low carbon heat, London, UK

Journal Articles1. Dodds PE, Staffell L, Hawkes AD, Li F, Grunewald P, McDowall

W, Ekins P, 2015, Hydrogen and fuel cell technologies for heating: A review,INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, Vol:40, Pages: 2065‐2083, ISSN: 0360‐3199

2. Xie C, Hawkes AD, 2015, Estimation of inter‐fuel substitution possibilities in China’s transport industryusing ridge regression, ENERGY, Vol: 88, Pages: 260‐267, ISSN: 0360‐5442

3. Hawkes AD, 2014, Long‐run marginal CO2 emissions factors in national electricity systems, APPLIED ENERGY, Vol: 125, Pages: 197‐205, ISSN: 0306‐2619

4. Kelly NJ, Tuohy PG, Hawkes AD, 2014, Performance assessment of tariff‐based air source heat pumpload shifting in a UK detached dwelling featuring phase change‐enhanced buffering, APPLIED THERMAL ENGINEERING, Vol: 71, Pages: 809‐820, ISSN: 1359‐4311

5. Pfenninger S, Hawkes A, Keirstead J, 2014, Energy systems modeling for twenty‐first century energy challenges, RENEWABLE & SUSTAINABLE ENERGY REVIEWS, Vol: 33, Pages: 74‐86, ISSN: 1364‐0321

Conference Contributions1. Hawkes AD, 2014, The taxonomy of energy systems

modelling, Energy Systems Conference2. Philbin SP, Jones D, Brandon NP, Hawkes AD, 2014,

Exploring Research Institutes: Structures,Functioning and Typology, Portland International Conference on Management of Engineering & Technology (PICMET), Publisher: IEEE, Pages: 2569‐2582, ISSN: 2159‐5100

3. Pinheiro L, Napp T, Hawkes AD, 2014, Can Brazil fulfil long term reduction targets? An evaluation of consequences of delayed action on its energy sector, 9th Conference on Sustainable Development of Energy, Water and Environmental Systems

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George Jackson

Professor of Chemical Physics, Department of Chemical Engineering, Imperial College London

Qualifications DPhil in Physical Chemistry, Exeter College, University of OxfordBSc Chemistry, Chelsea College, University of London

Awards and Distinctions Guggenheim Medal for Excellence in Thermodynamics, Institution of Chemical Engineers (IChemE, 2015)Fellow of the Mexican Academy of Molecular Engineering (2001)Fellow of the Royal Society of Chemistry (FRSC), Chartered Chemist (CChem, 1995)

Research InterestsA molecular description of matter is the key to understanding and predicting the properties of dense fluids and materials. The latest developments in statistical-mechanical theories and computer simulation (Monte Carlo and molecular dynamics) are used by my group to provide a reliable predictive platform for complex fluids and ordered materials at the molecular level. The focus is on thephase equilibria of systems which are of industrial relevance, e.g., mixtures containing hydrogen fluoride (production of refrigerants), aqueous solutions of surfactants (enhanced oil recovery), andhydrogen-bonded liquid crystals (optical devices).

One of our main achievements has been the development of a highly accurate equation of state for the thermodynamic properties of complex fluid mixtures: the statistical associating fluid theory forpotentials of variable range SAFT‐VR. We are currently embarking on extensions of the formalism to polymers, electrolytes, and inhomogeneous systems. A recent advance is the formation of theMolecular Systems Engineering (MSE) Group in which we are incorporating advanced thermodynamics modelling in process design and optimisation.

In the area of liquid-crystal modelling, the aim is a fundamental understanding of the effect of association, polar interactions and molecular flexibility on the stability of liquid-crystalline phases(nematic, biaxial, smectic, etc.). We are currently simulating molecules which incorporate molecular flexibility and dipolar interactions as well as chiral centres.

Other Activities1. 1991‐1996, Member of the Executive Committee of the Statistical Mechanics and Thermodynamics Group (SMTG) of the Faraday Division of the Royal Society of Chemistry2. 1992‐1998, Founder member of the Centre for Molecular Materials, Sheffield University3. 1993‐1996, Member of the Executive Committee of the Collaborative Computational Project 5 (CCP5)4. 1994‐1998, Editor of Molecular Physics5. 1995‐date, Fellow of the Royal Society of Chemistry, Chartered Chemist (FRSC, CChem)6. 1997‐2000, Member of Chemistry Programme (Structure and Bonding College) of the EPSRC7. 1998‐2013, Member of Executive Committee and Special Issue Editor of Molecular Physics8. 1998‐2002, Member of Editorial Board of Molecular Simulation9. 2000‐date, Member of Editorial Board of Fluid Phase Equilibria10. 2000‐2007, Member of Peer Review College of the EPSRC11. 2001‐date, Fellow of the Mexican Academy of Molecular Engineering12. 2003‐date, Member of the Centre for Process Systems Engineering13. 2003‐2009, Chairman of the Statistical Mechanics and Thermodynamics Group (SMTG) of the Faraday Division of the Royal Society of Chemistry14. 2006‐2011, Council Member of the Faraday Division of the Royal Society of Chemistry15. 2006‐2011, Member of the Faraday Standing Committee on Conferences16. 2006‐2013, Member of Management Committee of the Liquids and Complex Fluids Group of the Institute of Physics17. 2007‐2008, Member of Appointments Committee of the Department of Physics, University of Bergen, Norway18. 2007‐date, External Examiner, Physical Chemistry, Univ. of West Indies (Barbados, Jamaica, Trinidad and Tobago)19. 2007‐2013, UK Representative to European Federation of Chemical Engineering (EFCE), Thermodynamics/Transport20. 2008‐2011, Honorary Secretary and Treasurer of Faraday Council of the Royal Society of Chemistry

Reviewer forAIChE Journal, Chemical Physics Letters, Fluid Phase Equilibria, Industrial and Engineering Chemistry Research, Journal of the American Chemical Society, Journal of Chemical Physics, Journal of Physical Chemistry, Journal of Physics: Condensed Matter, Macromolecules, Molecular Physics, Molecular Simulation, Nature, Physical Chemistry, Chemical Physics, Physical Review Letters,Physical Review E.

Industrial CollaborationsBASF, BCURA, Power Ltd, Borealis AS, Britest Ltd., BP, ICI Research/Akzonobel, Ineos fluor/Mexichem, P&G, Pfizer, Novartis, Qatar Petroleum, Shell International, Schlumberger Syngenta, Total, Unilever Research.

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Publications Journal Articles1. GV Lau, PA Hunt, EA Müller, G Jackson, IJ Ford, 2015, Water

droplet excess free energy determined by cluster mitosis using guided molecular dynamics, Journal of Chemical Physics 143, 244709

2. B Rotenberg, G Jackson, D Frenkel, 2015, Jean‐Pierre Hansen – a stimulating history of simulating fluids, Molecular Physics 113, 2363‐2375

3. J Jover, A Galindo, G Jackson, EA Müller, AJ Haslam, 2015, Fluid–fluid coexistence in an athermal colloid–polymer mixture: thermodynamic perturbation theory and continuum molecular‐dynamics simulation, Molecular Physics 113, 2608‐2628

4. L Wu, A Malijevský, G Jackson, EA Müller, C Avendaño, 2015, Orientational ordering and phase behaviour of binary mixtures of hard spheres and hard spherocylinders, Journal of Chemical Physics 143, 044906

5. S Dufal, T Lafitte, AJ Haslam, A Galindo, GNI Clark, C Vega, G Jackson, 2015, The A in SAFT: developing the contribution of association to the Helmholtz free energy within a Wertheim TPT1 treatment of generic Mie fluids, Molecular Physics 113, 948‐984

6. J Burger, V Papaioannou, S Gopinath, G Jackson, A Galindo, CS Adjiman, 2015, A hierarchical method to integrated solvent and process design of physical CO2 absorption using the SAFT‐γ Mie approach, AIChE Journal 61, 3249‐3269

7. GV Lau, IJ Ford, PA Hunt, EA Müller, G Jackson, 2015, Surface thermodynamics of planar, cylindrical, and spherical vapour‐liquid interfaces of water, Journal of Chemical Physics 142, 114701

8. Lobanova, C Avendaño, T Lafitte, EA Müller, G Jackson, 2015, SAFT‐γ force field for the simulation of molecular fluids: 4. A single‐site coarse‐grained model of water applicable over a wide temperature range, Molecular Physics 113, 1228‐1249

9. S Dufal, T Lafitte, A Galindo, G Jackson, AJ Haslam, 2015, Developing intermolecular‐potential models for use with the SAFT‐VR Mie Equation of State, AIChE Journal 61, 2891‐2912

10. JF Jover, EA Müller, AJ Haslam, A Galindo, G Jackson, H Toulhoat, et al. 2015, Aspects of asphaltene aggregation obtained from coarse‐grained molecular modelling, Energy & Fuels 29, 556–566

11. G Jackson, GV Lau, EA Müller, PA Hunt, IJ Ford, 2015, Water droplet excess free energy determined by cluster mitosis using guided molecular dynamics, American Institute of Physics (AIP)

12. FE Pereira, A Galindo, G Jackson, CS Adjiman, 2014, On the impact of using volume as an independent variable for the solution of P‐T fluid‐phase equilibrium with equations of state, Computers & Chemical Engineering 71, 67‐76

13. F Coletti, BD Crittenden, AJ Haslam, GF Hewitt, G Jackson, et al. 2014, Modeling of fouling from molecular to plant scale, Elsevier Inc.

14. JMA Schreckenberg, S Dufal, AJ Haslam, CS Adjiman, G Jackson, et al. 2014, Modelling of the thermodynamic and solvation properties of electrolyte solutions with the statistical associating fluid theory for potentials of variable range, Molecular Physics 112, 2339‐2364

15. S Dufal, V Papaioannou, M Sadeqzadeh, T Pogiatzis, A Chremos, et al. 2014, Prediction of thermodynamic properties and phase behavior of fluids and mixtures with the SAFT‐γ Mie groupcontribution equation of state, Journal of Chemical & Engineering Data 59, 3272‐3288

16. EA Müller, G Jackson, 2014, Force field parameters from the SAFT‐γ equation of state for use in coarsegrained molecular simulations, Annual Review of Chemical and Biomolecular Engineering 5, 405‐427

17. L Wu, EA Müller, G Jackson, 2014, Understanding and describing the liquid‐crystalline states of polypeptide solutions: A coarse‐grained model of PBLG in DMF, Macromolecules 47, 1482‐1493

18. V Papaioannou, T Lafitte, C Avendaño, CS Adjiman, G Jackson, et al. 2014, Group contribution methodology based on the statistical associating fluid theory for heteronuclear molecules formed from Mie segments, Journal of Chemical Physics 140, 054107

19. L Lu, S Wang, EA Müller, W Cao, Y Zhu, X Lu, G Jackson, 2014, Adsorption and separation of CO2+CH4 mixtures using nanoporous adsorbents by molecular simulation, Fluid Phase Equilibria 362, 227‐234

20. AI Papadopoulos, S Badr, A Chremos, E Forte, T Zarogiannis, P Seferlis, et al. 2014, Efficient screening and selection of post‐combustion CO2 capture solvents, Chemical Engineering Transactions 39, 211‐216

21. CS Adjiman, A Galindo, G Jackson, 2014, Molecules matter: The expanding envelope of process design, Computer Aided Chemical Engineering 34, 55

22. E Forte, AJ Haslam, G Jackson, EA Müller, 2014, Effective coarse‐grained solid–fluid potentials and their application to model adsorption of fluids on heterogeneous surfaces, Physical Chemistry Chemical Physics 16, 19165‐19180

Keynote/plenary talks given at international conferences1. 2014 “Computing the Pressure and Interfacial Tension of

Inhomogenenous Nanoscopic Systems Including Drops and Confined Anisotropic Phases: The Devil Is in the Detail,” Annual AIChE Meeting, Atlanta, USA.

2. 2015 “Coarse Grained Modelling of the Phase Behaviour of Non‐Ionic Surfactants,.” British Liquid Crystal Conference, Sheffeild.

3. 2015 “SAFT‐γ force fields for molecular simulations of the thermodynamic, structural and transport properties of complex fluids and mixtures,” SAFT 25th Anniversary Conference, Houston, USA.

4. 2015 “Guggenheim Medal Award: The legacy of Edward Guggenheim to Statistical Thermodynamics,” Thermodynamics 2015 Conference, Copenhagen, Denmark

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James Keirstead

Lecturer in Urban Energy Systems, Department of Civil and Environmental Engineering, Imperial College London

Qualifications BSc in Civil Engineering (First Class Honours, Queen’s University, Canada), MSc Environmental Change and Management (Distinction, University of Oxford)DPhil (University of Oxford).

Awards and Distinctions Chartered Engineer, Member of the Energy InstituteCommonwealth Scholar, 2003-2006British Council Chevening Scholar, 2001-2002Guinness Book of World Records, 2000, Longest Distance Travelled by Solar Powered Vehicle

SecondmentsOctober 2010, University of Tokyo, Institute for Industrial Science.

Research Interests1. Urban energy systems including systems integration, technologies, and policies2. Optimisation methods, agent-based simulation, uncertainty/ sensitivity analysis3. Industrial ecology, particularly urban metabolism

Other ActivitiesElected board member, Sustainable Urban Systems section, International Society for Industrial Ecology Technical committee member, ISIE and ATES conferences, proposal peer review for EPSRC, ESRC, US National Science Foundation, Natural Sciences and Engineering and Social Sciences and Humanities Research Councils of Canada.

Reviewer ActivitiesEnergy Policy, Proceedings of the National Academy of Sciences, Building Research and Information, Technological Forecasting and Social Change, Energy, Energy Economics, Journal of Artificial Societies and Social Simulation, Energy Efficiency, The Energy Journal, Journal of Industrial Ecology, Computers, Environment and

Urban Systems, Journal of Urban Technology, International Journal of Sustainable Transportation, Climatic Change, Urban Design and Planning, Environmental Science & Technology, IET Renewable Power Generation, Environment and Planning B, Ecological Modelling, Environmental Research Letters, and others.

Academic CollaborationsUniversity of Toronto, Prof. Chris KennedyUniversity of Minnesota, Prof. Anu RamaswamiArizona State University, Dr. Mikhail ChesterUniversity of Surrey, Prof. Roland CliftUniversity of Bath, Dr Nick McCullen

Industrial CollaborationsArup, AECOM, Hildebrand Ltd

Alexandros Kiparissides

Lecturer in the Department of Biochemical Engineering, University College London

Qualifications Diploma in Chemical Engineering (Aristotle University of Thessaloniki, Greece) PhD in Bioprocess Systems Engineering (Imperial College London, UK)

Research InterestsRecombinant protein production in mammalian cell cultures, algae biotechnology and bioprocessing. Development of an integrated methodology combining Multi‐scale & Metabolic Modelling, Metabolic Engineering and wet‐lab experiments in order to: (i) Better understand cell physiology and metabolism under industrial bioprocessing conditions; (ii) Identify key parameters affecting culture efficiency at the metabolic, bioprocess and reactor design level; (iii) Enable the model based design and optimisation of industrial scale bioreactors.

Other ActivitiesMember of the SIG: Biochemical Engineering – IChemEMSc Admissions Tutor – Department of Biochemical Engineering, UCL

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Reviewer forBiochemical Engineering JournalBMC BioinformaticsChemical Engineering Research and Design Computers & Chemical EngineeringAlgal Research, TechnologyBiomass & Bioenergy

Academic CollaborationsImperial College London (UK), University College Dublin (IRL), University of Surrey (UK), Tufts University (USA), École Polytechnique Fédérale de Lausanne ‐ EPFL (CH), Austrian Centre of Industrial Biotechnology (AUT), Cyprus University of Technology (CY), Centre for Research and Technology Hellas (GR).

Industrial CollaborationsLonza Biologics Medimmune

Publications Journal Articles1. Kiparissides A., Pistikopoulos E.N., Mantalaris A., Georgakis

C. (2014). In‐Silico Design of Experiments as a Tool for Nonlinear Sensitivity Analysis of Detailed Models. Ind. Eng. Chem. Res., v.53(18), pp: 7517–7525

2. Kiparissides A., Pistikopoulos E.N., Mantalaris A. (2015). On the Model Based Optimisation of Monoclonal Antibody Production in GS‐NS0 Cell Cultures. Biotechnology & Bioengineering, v.112(3), pp: 536‐548

3. Kiparissides A., Hatzimanikatis V. (2015). Thermodynamics‐based Metabolite Sensitivity Analysis in Metabolic Networks. Metabolic Engineering, Under Revision

Conference Presentations and Posters1. Vieira Pinto J., Kiparissides A., Hatzimanikatis V. (2014).

“Characterization of intracellular metabolic states presenting the Warburg phenotype”, COBRA 2014 ‐ 3rd Conference on Constraint‐Based Reconstruction and Analysis, Charlottesville (VA), USA.

2. Kiparissides A., Hatzimanikatis V. (2014). “Deciphering thermodynamics in metabolic networks: A priority list of candidates for metabolomics”, Metabolic Engineering X, Vancouver (BC), Canada.

3. Kiparissides A., Hatzimanikatis V. (2015). “Reducing uncertainty in metabolic networks through thermodynamics based flux analysis”, 5th ICBE—International Conference on Biomolecular Engineering, Austin (TX), USA.

Cleo Kontoravdi

Senior Lecturer, Department of Chemical Engineering, Imperial College London

QualificationsPhD in Chemical Engineering, Imperial College London MEng in Chemical Engineering, Imperial College London

Research InterestsMathematical modelling, experiment design and optimisation for biological processes Protein‐producing animal cell culturesProtein glycosylation

Industrial CollaborationsLonza Biologics MedImmuneGSK Symphogen

Reviewer forBiotechnology ProgressBiotechnology and BioengineeringAnalytical BiochemistryBiochemical Engineering JournalPLoS ONECytotechnologyBiotechnology and Applied BiochemistryBioprocess and Biosystems EngineeringChemical Engineering ScienceComputer Applications in BiotechnologyBiochemical Engineering Journal

Publications Journal Articles1. Sou SN, Sellick C, Lee K, Mason A, Kyriakopoulos S, Polizzi

KM, Kontoravdi C, 2015, How does mild hypothermia affect monoclonal antibody glycosylation?, Biotechnology and Bioengineering, 112: 1165‐1176

2. Fan Y, Del Val IJ, Muller C, Lund AM, Sen JW, Rasmussen SK, Kontoravdi C, Baycin‐Hizal D, Betenbaugh MJ, Weilguny D, Andersen MR, 2015, A multi‐pronged investigation into the effect of glucose starvation and culture duration on fed‐batch

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CHO cell culture, Biotechnology and Bioengineering, 112: 2172‐ 2184

3. Polizzi KM, Kontoravdi C, 2015, Genetically‐encoded biosensors for monitoring cellular stress in bioprocessing, Current Opinion in Biotechnology, 31: 50‐56

4. Fan Y, Jimenez del Val I, Muller C, Sen JW, Rasmussen SK, Kontoravdi C, Weilguny D, Andersen MR, 2015, Amino acid and glucose metabolism in fed‐batch CHO cell culture affects antibody production and glycosylation, Biotechnology and Bioengineering, 112: 521‐535

5. Oliveira PH, Mairhofer J, Alves PM, Lara AR, Kontoravdi C, 2015, Advances in the Development of Biotherapeutics, BioMed Research International, Article ID 793876

6. Jedrzejewski PM, Jimenez del Val I, Constantinou A, Dell A, Haslam SM, Polizzi KM, Kontoravdi C, 2014, Towards Controlling the Glycoform: A Model Framework Linking Extracellular Metabolites to Antibody Glycosylation, International Journal of Molecular Sciences, 15: 4492‐4522

7. Kyriakopoulos S, Kontoravdi C, 2014, A framework for the systematic design of fed‐batch strategies in mammalian cell culture, Biotechnology and Bioengineering, 111: 2466‐2476

8. Niu H, Leak D, Shah N, Kontoravdi C, 2014, Metabolic characterization and modeling of fermentation process of an engineered Geobacillus thermoglucosidasius strain for bioethanol production with gas stripping, Chemical Engineering Science, 122: 138‐149

9. Todri E, Amenaghawon AN, del Val IJ, Leak DJ, Kontoravdi C, Kucherenko S, Shah N, 2014, Global sensitivity analysis and meta‐modeling of an ethanol production process, Chemical Engineering Science, 114: 114‐127

10. Kyriakopoulos S, Kontoravdi C, 2014, Insights on biomarkers from Chinese hamster ovary ‘omics’ studies, Pharmaceutical Bioprocessing, 2: 389‐401

11. Behjousiar A, Constantinou A, Polizzi KM, Kontoravdi C, 2014, FIBS‐enabled Noninvasive Metabolic Profiling, Jove‐Journal of Visualized Experiments, doi:10.3791/51200

Invited talks2nd BioProNet Symposium, Manchester, U.K., October 2015Cell Line Development & Engineering, Vienna, Austria, February 2014.

J Krishnan

Senior Lecturer, Department of Chemical Engineering, Imperial College London. Affiliated with: Institute for Systems and Synthetic Biology, Centre for Bioinformatics

Qualifications B.Tech Indian Institute of Technology, MadrasPh.D Princeton University (Chemical Engg)Associate Research Scientist, Electrical Engg, Johns Hopkins University

Research InterestsInformation processing in cells and tissues with applications in systems and synthetic biology combining (i) mathematical modelling (ii) theoretical work (iii) systems analysis including tool development (iv) experimental collaboration. Mathematical modelling involves temporal, spatial and stochastic descriptions as appropriate, and some of the mathematical modelling is explicitly multi‐level (e.g., cells and tissues). This is complemented by theoretical and systems work involving tools from dynamical systems, systems engineering, control engineering, and network analysis. Modelling and systems analysis spans a whole range of levels and scales from the enzymatic (multi‐site phosphorylation), to the gene regulatory (mRNA translation), to the network (information processing in network modules, regulation of the cell cycle in dynamic environments, spatial control of biochemical cascades and pathways), to the cell and tissue levels (effect of intrinsic and induced drug resistance mechanisms at the cell and tissue scales, engineering of patterns at the tissue level). We are also interested in non‐biological analogues of such work in engineered and related physico‐chemical systems.

Reviewer forSystems and Synthetic BiologyPLOS Computational Biology, Biophysical Journal, Journal of Theoretical Biology, Integrative Biology, Interface Journal of the Royal Society, Wiley Interdisciplinary Reviews in Systems Biology and Medicine, Biochemical Engineering Journal, IET Systems Biology, BMC Systems Biology, BMC Research Notes, Physical Biology,

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Advances in Systems Biology (book), IEEE Transactions in NanoBioscience, Molecular Biosystems, Journal of Chemical Physics.

Biomedical Engineering Annals of Biomedical Engineering, Fundamental and Clinical Pharmacology.

Dynamical Systems/Control/Systems EnggIEEE Transactions on Automatic Control, Automatica,Computers and Chemical Engineering, Chemical Engineering Research and Design.

Academic CollaborationsCollaborations with experimental groups in systems and synthetic biology (mRNA translation, cell signalling and decision making, spatial engineering at cell and tissue levels).

Publications Journal Articles1. Alam‐Nazki A, Krishnan J, 2015, Spatial Control of

Biochemical Modification Cascades and Pathways, BIOPHYSICAL JOURNAL, Vol: 108, Pages: 2912‐2924, ISSN: 0006‐3495

2. Liu C, Krishnan J, Xu XY, 2015, Intrinsic and induced drug resistance mechanisms: in silico investigations at the cellular and tissue scales, INTEGRATIVE BIOLOGY, Vol: 7, Pages: 1044‐1060, ISSN: 1757‐9694

3. Suwanmajo T, Krishnan J, 2015, Mixed mechanisms of multi‐site phosphorylation, JOURNAL OF THE ROYAL SOCIETY INTERFACE, Vol: 12, Article number: 20141405, ISSN: 1742‐5689

4. Zhao Y‐B, Krishnan J, 2015, Probabilistic Boolean Modeling and Analysis framework for mRNA translation, IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, Volume: 13, Pages 754-766 ISSN: 1557‐9964

5. Krishnan J, Mois K, Suwanmajo T, 2014, The behaviour of basic autocatalytic signalling modules in isolation and embedded in networks, JOURNAL OF CHEMICAL PHYSICS, Vol: 141, Article number: 175102, ISSN: 0021‐9606

6. Liu C, Krishnan, Xu XY, 2014, Towards an integrated systems‐based modelling framework for drug transport and its effect on tumour cells, JOURNAL OF BIOLOGICAL ENGINEERING, Vol: 8, ISSN: 1754‐ 1611

7. Zhao Y‐B, Krishnan J, 2014, mRNA translation and protein synthesis: an analysis of different modelling methodologies and a new PBN based approach, BMC SYSTEMS BIOLOGY, Vol: 8, ISSN: 1752‐0509

Book Chapters1. Krishnan J, Liu C, 2014, An investigation of signal

transduction and irreversible decision making through monostable and bistable switches, A Systems Theoretic Approach to Systems and Synthetic Biology II: Analysis and Design of Cellular Systems, Pages: 219‐243, ISBN: 9789401790468

Niall Mac Dowell

Lecturer in Energy and Environmental Technology and Policy, Centre for Environmental Policy, Imperial College London

Qualifications PhD in Chemical Engineering, Imperial College London (2010) B.E. in Chemical Engineering, University College Dublin, (2005)

Awards and DistinctionsNicklin Medal, Institution of Chemical Engineers, 2015Chartered Chemical Engineer, CEng, Institution of Chemical Engineers, 2013The Qatar Petroleum Award for PhD Research Excellence in Clean Fossil Fuels, QatarPetroleum, 2010

Research InterestsClean Fossil FuelsCarbon Capture and Storage (CCS)Low carbon electricity generationBiomass Enhanced Carbon Capture and Storage (BECCS) CO2 Capture and utilisation (CCu)Ionic liquidsDynamic Process Modelling, Simulation and Optimisation Mathematical Modelling

Other ActivitiesVisiting Academic in the Department of Mechanical Engineering, University of Sheffield Secretary of the Executive Board of the IChemE Energy CentreAppointed to the TechnicalWorking Group of the Zero Emissions Platform (ZEP) Appointed to the Technical Working Group of the Carbon Capture and Storage Association Member, Royal Society of Chemistry, 2015MAIChE, American Institution of Chemical Engineers, 2008 MIChemE, Institution of Chemical Engineers, 2004

Reviewer forEnergy and Environmental ScienceMolecular Systems Design and Engineering

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PublicationsJournal Articles1. Brown S, Mahgerefteh H, Martynov S, Sundara V, Mac Dowell

N, 2015, A multi‐source flow model for CCS pipeline transportation networks, INTERNATIONAL JOURNAL OF GREENHOUSE GAS CONTROL, Vol: 43, Pages: 108‐114, ISSN: 1750‐5836

2. Mac Dowell N, Shah N, 2015, The multi‐period optimisation of an amine‐based CO2 capture process integrated with a super‐critical coal‐fired power station for flexible operation, COMPUTERS & CHEMICAL ENGINEERING, Vol: 74, Pages: 169‐183, ISSN: 0098‐ 1354

3. Mac Dowell N, Staffell I, 2015, The role of flexible CCS in the UK’s future energy system, International Journal of Greenhouse Gas Control, ISSN: 1750‐5836

4. Martynov S, Mac Dowell N, Brown S, Mahgerefteh H, 2015, Assessment of Integral Thermo‐Hydraulic Models for Pipeline Transportation of Dense‐Phase and Supercritical CO2, INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, Vol: 54, Pages: 8587‐8599, ISSN: 0888‐5885

5. A. Buchard, M. North, C. Kozak, E. Remiezowicz, P. Abrantes, A. Bardow, J. Dodson, C.Williams, J. Albo, I. Ingram, G. V. S. M. Carrera, P. Styring, M. Poliakoff, K. Lamb, E. A. Quadrelli, N. Mac Dowell, G. Dowson, M. Aresta, R. Heyn, J. A. Castro‐Osma, W. Webb, R. Silva, A. Marciniak, C. Jones, C. T. Yavuz, C. Capacchione, A. Coogan, M. Priestnall, “Atom efficiency in small molecule and macromolecule synthesis: general discussion”, Faraday discussions, 2015, 183, 97‐123 5. C. Jones, K. Armstrong, I. Ingram, E. Bay, J. Dodson, P. Abrantes, M. North, P. Styring, N. Mac Dowell, D. Churina, K. Lamb, M. Aresta, G. Dowson, R. Heyn, E. A. Quadrelli, R. Silva, A. Marciniak, N. Meine, K. Dossumov, A. Navarrete, A. Bardow, A. Coogan, E. Fraga, “Wider Impacts: general discussion”, Faraday discussions, 2015, 183, 349‐368

6. Akgul O, Mac Dowell N, Papageorgiou LG, Shah N, 2014, A mixed integer nonlinear programming (MINLP) supply chain optimisation framework for carbon negative electricity generation using biomass to energy with CCS (BECCS) in the UK, INTERNATIONAL JOURNAL OF GREENHOUSE GAS CONTROL, Vol: 28, Pages: 189‐202, ISSN: 1750‐5836

7. Boot‐Handford ME, Abanades JC, Anthony EJ, Blunt MJ, Brandani S, Mac Dowell N, Fernandez JR, Ferrari M‐C, Gross R, Hallett JP, Haszeldine RS, Heptonstall P, Lyngfelt A, Makuch Z, Mangano E, Porter RTJ, Pourkashanian M, Rochelle GT, Shah N, Yao JG, Fennell PS, 2014, Carbon capture and storage update, ENERGY & ENVIRONMENTAL SCIENCE, Vol: 7, Pages: 130‐189, ISSN: 1754‐5692

8. Chen L, Sharifzadeh M, Mac Dowell N, Welton T, Shah N, Hallett JP, 2014, Inexpensive ionic liquids: [HSO4] ̄‐based solvent production at bulk scale, GREEN CHEMISTRY, Vol: 16, Pages: 3098‐3106, ISSN: 1463‐9262

9. Mac Dowell N, Llovell F, Sun N, Hallett JP, George A, Hunt PA, Welton T, Simmons BA, Vega LF, 2014, New Experimental Density Data and soft‐SAFT Models of Alkylimidazolium ([CnC1im](+)) Chloride (Cl‐), Methylsulfate ([MeSO4](‐)), and Dimethylphosphate ([Me2PO4](‐)) Based Ionic Liquids, JOURNAL OF PHYSICAL CHEMISTRY B, Vol: 118, Pages: 6206‐6221, ISSN: 1520‐6106

10. Mac Dowell N, Shah N, 2014, Dynamic modelling and analysis of a coal‐fired power plant integrated with a novel split‐flow configuration post‐combustion CO2 capture process, International Journal of Greenhouse Gas Control, Vol: 27, Pages: 103‐119, ISSN: 1750‐ 5836

Conference Contributions1. Mehleri ED, Mac Dowell N, Thornhill NF, 2015, Model

Predictive Control of Post‐Combustion CO2 Capture Process integrated with a power plant, 12th International Symposium on Process Systems Engineering (PSE) / 25th European Symposium on Computer Aided Process Engineering (ESCAPE), Publisher: ELSEVIER SCIENCE BV, Pages: 161‐166, ISSN: 1570‐7946

2. Brown S, Martynov S, Mahgerefteh H, Fairweather M, Woolley RM, Wareing CJ, Falle SAEG, Rutters H, Niemi A, Zhang YC, Chen S, Besnebat J, Shah N, Mac Dowell N, Proust C, Farret R, Economou IG, Tsangaris DM, Boulougouris GC, Van Wittenberghe J, 2014, CO(2)QUEST: Techno‐economic assessment of CO2 quality effect on its storage and transport, 12th International Conference on Greenhouse Gas Control Technologies (GHGT), Publisher: ELSEVIER SCIENCE BV, Pages: 2622‐2629, ISSN: 1876‐6102

3. Lucquiaud M, Fernandez ES, Chalmers H, Mac Dowell N, Gibbins J, 2014, Enhanced operating flexibility and optimised off‐design operation of coal plants with post‐combustion capture, 12th International Conference on Greenhouse Gas Control Technologies (GHGT), Publisher: ELSEVIER SCIENCE BV, Pages: 7494‐7507, ISSN: 1876‐6102

4. Mac Dowell N, Shah N, 2014, Optimisation of post‐combustion CO2 capture for flexible operation, 12th International Conference on Greenhouse Gas Control Technologies (GHGT), Publisher: ELSEVIER SCIENCE BV, Pages: 1525‐1535, ISSN: 1876‐6102

Invited Lectures and Seminars1. CO2 capture and storage without the Geography, Alternative

Carbon Capture and Storage (CCS) Pathways Workshop, June 2014, St Catherine’s College, Oxford

2. On the use of advanced association theories in process engineering, SAFT Meeting 2014, April 2014, Tróia, Portugal

3. Optimisation of post‐combustion CO2 capture forflexible operation, keynote lecture at UKCCSRC Biannual meeting, April 2014, Queens’ College Cambridge, UK

4. UK power generation: carbon source or sink?, UKCCSRC workshop on Direct Air/Negative Emissions, March 2014, Imperial College London

5. Optimisation of post‐combustion CCS for flexible operation,14th Advanced Power Generation Technology Forum (APGTF) Workshop, April 2014, 1VS Conference Centre, Westminster, London, UK

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Geoffrey C. Maitland FREng

Professor of Energy Engineering, Department of Chemical Engineering, Imperial College London

Qualifications MA in Chemistry (Oxford University)DPhil in Physical Chemistry (Oxford University)

Awards and DistinctionsFellow of the Royal Academy of Engineering Fellow of the IChemEPresident of IChemE 2014‐15Fellow of the Royal Society of Chemistry Salters’ Scholar 1969‐72ICI Fellowship 1972‐74Hutchison Medal of the IChemE, 1999 IChemE Envoy Award 2010RSC/SCI Rideal Award 2012

Research InterestsClean production and use of fossil fuelsCarbon capture and storageRecovery of non‐conventional hydrocarbonsReal‐time control and management of oil and gas reservoirs Thermophysical properties of fluids Rheology of complex fluids and soft materialsRock‐fluid interactionsRenewable solar production of hydrogen from water using green algae and cyanobacteria

Other ActivitiesPresident, Institution of Chemical Engineers 2014‐15Deputy President, Institution of Chemical Engineers 2013‐14EPSRC: Member of Peer Review CollegeEditor, Chemical Engineering Research and Development Soft Matter Journal: Founder Member of Editorial BoardMember of IChemE Council and UK BoardMember of Royal Society of Chemistry Publications Board Member of Royal Society of Chemistry FaradayCouncil with responsibility for liaison with IChemE Associate Member University of Wales Institute of Non‐Newtonian Fluid MechanicsChair, EPSRC Steering Group, Portfolio Grant on Complex Fluids and Complex Flows, Swansea UniversityChair, UK Offshore Oil and Gas Regulatory Review Panel

Reviewer forACS Petroleum Research FundChemical Engineering Research and Development Chemical Engineering Science Journal of Chemical and Engineering DataJournal of Materials ChemistryJournal of Non‐Newtonian Fluid Mechanics Journal of Rheology LangmuirMolecular Physics NaturePhysical Chemistry Chemical Physics Soft Matter

Publications Journal Articles1. Al Ghafri SZS, Forte E, Galindo A, Maitland GC, Trusler JPM,

2015, Experimental and Modeling Study of the Phase Behavior of (Heptane plus Carbon Dioxide plus Water) Mixtures, JOURNAL OF CHEMICAL AND ENGINEERING DATA, Vol: 60, Pages: 3670‐3681, ISSN: 0021‐ 9568

2. Bailey L, Lekkerkerker HNW, Maitland GC, 2015, Smectite clay ‐ inorganic nanoparticle mixed suspensions: phase behaviour and rheology, SOFT MATTER, Vol: 11, Pages: 222‐236, ISSN: 1744‐683X

3. Cadogan SP, Hallett JP, Maidand GC, Trusler JPM, 2015, Diffusion Coefficients of Carbon Dioxide in Brines Measured Using C‐13 Pulsed‐Field Gradient Nuclear Magnetic Resonance, JOURNAL OF CHEMICAL AND ENGINEERING DATA, Vol: 60, Pages: 181‐184, ISSN: 0021‐9568

4. Dechatiwongse P, Maitland G, Hellgardt K, 2015, Demonstration of a two‐stage aerobic/anaerobic chemostat for the enhanced production of hydrogen and biomass from unicellular nitrogen‐fixing cyanobacterium, ALGAL RESEARCH‐BIOMASS BIOFUELS AND BIOPRODUCTS, Vol: 10, Pages: 189‐201, ISSN: 2211‐9264

5. Hou S‐X, Maitland GC, Trusler JPM, 2015, Phase equilibria of (CO2 + butylbenzene) and (CO2 + butylcyclohexane) at temperatures between (323.15 and 423.15) K and at pressures up to 21 MPa, FLUID PHASE EQUILIBRIA, Vol: 387, Pages: 111‐116, ISSN: 0378‐3812

6. Maitland G, 2015, Refining in the reservoir, TCE The Chemical Engineer, Pages: 32‐35, ISSN: 0302‐0797

7. McBride‐Wright M, Maitland GC, Trusler JPM, 2015, Viscosity and Density of Aqueous Solutions of Carbon Dioxide at Temperatures from (274 to 449) K and at Pressures up to 100 MPa, JOURNAL OF CHEMICAL AND ENGINEERING DATA, Vol: 60, Pages: 171‐180, ISSN: 0021‐ 9568

8. Peng C, Crawshaw JP, Maitland GC, Trusler JPM, 2015, Kinetics of calcite dissolution in CO2‐saturated water at temperatures between (323 and 373) K and pressures up to 13.8 MPa, CHEMICAL GEOLOGY, Vol: 403, Pages: 74‐85, ISSN: 0009‐2541

9. Remiezowicz E, Spooren J, Bay E, Cowan A, Ingram I, Abrantes P, Nunes da Ponte M, North M, Albo J, Styring P, Priestnall M, Lamb K, Aresta M, Quadrelli EA, Heyn R, Bardow A, Webb W, Silva R, Alonso‐Moreno C, Janaky C, Maitland G, Vaidyanathan S, Carrera GV, Reed D, Vanbroekhoven K, Yavuz CT, Pant D, Hollingsworth N, 2015, Capture agents, conversion mechanisms, biotransformations and biomimetics:

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general discussion., Faraday Discuss, Vol: 183, Pages: 463‐487, ISSN: 1359‐6640

10. Schmidt KAG, Pagnutti D, Curran MD, Singh A, Trusler JPM, Maitland GC, McBride‐Wright M, 2015, New Experimental Data and Reference Models for the Viscosity and Density of Squalane, JOURNAL OF CHEMICAL AND ENGINEERING DATA, Vol: 60, Pages: 137‐150, ISSN: 0021‐9568

11. Zhang D, Dechatiwongse P, Del‐Rio‐Chanona EA, Hellgardt K, Maitland GC, Vassiliadis VS, 2015, Analysis of the cyanobacterial hydrogen photoproduction process via model identification and process simulation, CHEMICAL ENGINEERING SCIENCE, Vol: 128, Pages: 130‐146, ISSN: 0009‐2509

12. Zhang D, Dechatiwongse P, del Rio‐Chanona EA, Maitland GC, Hellgardt K, Vassiliadis VS, 2015, Modelling of light and temperature influences on cyanobacterial growth and biohydrogen production, ALGAL RESEARCH‐BIOMASS BIOFUELS AND BIOPRODUCTS, Vol: 9, Pages: 263‐274, ISSN: 2211‐9264

13. Zhang D, Dechatiwongse P, del Rio‐Chanona EA, Maitland GC, Hellgardt K, Vassiliadis VS, 2015, Dynamic modelling of high biomass density cultivation and biohydrogen production in different scales of flat plate photobioreactors, BIOTECHNOLOGY AND BIOENGINEERING, Vol: 112, Pages: 2429‐2438, ISSN: 0006‐3592

14. del Rio‐Chanona EA, Dechatiwongse P, Zhang D, Maitland GC, Hellgardt K, Arellano‐Garcia H, Vassiliadis VS, 2015, Optimal Operation Strategy for Biohydrogen Production, INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, Vol: 54, Pages: 6334‐6343, ISSN: 0888‐5885

15. Al Ghafri SZS, Maitland GC, Trusler JPM, 2014, Experimental and modeling study of the phase behavior of synthetic crude oil + CO2, FLUID PHASE EQUILIBRIA, Vol: 365, Pages: 20‐40, ISSN: 0378‐3812

16. Al Ghafri SZS, Forte E, Maitland GC, Rodriguez‐Henriquez JJ, Trusler JPM, 2014, Experimental and Modeling Study of the Phase Behavior of (Methane + CO2 + Water) Mixtures, JOURNAL OF PHYSICAL CHEMISTRY B, Vol: 118, Pages: 14461‐14478, ISSN: 1520‐ 6106

17. Bailey L, Lekkerkerker HNW, Maitland GC, 2014, Rheology modification of montmorillonite dispersions by colloidal silica, RHEOLOGICA ACTA, Vol: 53, Pages: 373‐384, ISSN: 0035‐4511

18. Cadogan SP, Maitland GC, Trusler JPM, 2014, Diffusion Coefficients of CO2 and N‐2 in Water at Temperatures between 298.15 K and 423.15 K at Pressures up to 45 MPa, JOURNAL OF CHEMICAL AND ENGINEERING DATA, Vol: 59, Pages: 519‐525, ISSN: 0021‐9568

19. Dechatiwongse P, Srisamai S, Maitland G, Hellgardt K, 2014, Effects of light and temperature on the photoautotrophic growth and photoinhibition of nitrogen‐fixing cyanobacterium Cyanothece sp ATCC 51142, ALGAL RESEARCH‐BIOMASS BIOFUELS AND BIOPRODUCTS, Vol: 5, Pages: 103‐111, ISSN: 2211‐9264

20. Maitland G, 2014, Putting CO2 in its place, TCE The Chemical Engineer, Pages: 34‐37, ISSN: 0302‐0797

Athanasios (Sakis) Mantalaris

Professor in BioSystems Engineering, Department of Chemical Engineering, Imperial College London

Qualifications PhD in Chemical Engineering, University of Rochester MSc in Chemical Engineering, University of Rochester

Awards and DistinctionsFellow of the American Institute of Biological and Medical Engineers 2013European Research Council Advanced Investigator Award 2012Fellow, American Institute of Medical & Biological Engineering, 20111st Prize Award, Hellenic Association of Orthopaedics Surgery & Traumatology, 2009Rector’s Award for Research Excellence, Imperial College, 2006Live Demo Award, ISCAS, 2006Jounitor Moulton Award, IChemE, 2004

Research InterestsModelling of Biological Systems, Mammalian Cell Bioprocessing, Stem Cell Bioprocessing and Tissue Engineering.

Other ActivitesMember of the Executive Board of the European Society for Biochemical Engineering Sciences (ESBES)Member of the Advisory Board for Prometheus Catholic University of Leuven

Reviewer forTissue EngineeringBiomaterials, Stem Cells & DevelopmentBiochemical Engineering JournalBiotechnology & Bioengineering

Academic CollaborationsUniversity of Thessaloniki ETHTemple UniversityNTU

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Industrial CollaborationsNovalung

PublicationsJournal Articles1. Kang Y, Georgiou AI, MacFarlane RJ, Klontzas ME, Heliotis M,

Tsiridis E, Mantalaris A, 2015, Fibronectin stimulates the osteogenic differentiation of murine embryonic stem cells., J Tissue Eng Regen Med

2. Kiparissides A, Pistikopoulos EN, Mantalaris A, 2015, On the Model‐Based Optimization of Secreting Mammalian Cell (GS‐NS0) Cultures, BIOTECHNOLOGY AND BIOENGINEERING, Vol: 112, Pages: 536‐548, ISSN: 0006‐3592

3. Muenzer DGG, Ivarsson M, Usaku C, Habicher T, Soos M, Morbidelli M, Pistikopoulos EN, Mantalaris A, 2015, An unstructured model of metabolic and temperature dependent cell cycle arrest in hybridoma batch and fed‐batch cultures, BIOCHEMICAL ENGINEERING JOURNAL, Vol: 93, Pages: 260‐273, ISSN: 1369‐703X

4. Fauzi I, Panoskaltsis N, Mantalaris A, 2014, Early Exposure of Murine Embryonic Stem Cells to Hematopoietic Cytokines Differentially Directs Definitive Erythropoiesis and Cardiomyogenesis in Alginate Hydrogel Three‐Dimensional Cultures, STEM CELLS AND DEVELOPMENT, Vol: 23, Pages: 2720‐2729, ISSN: 1547‐3287

5. Fuentes‐Gari M, Misener R, Garcia‐Munzer D, Velliou E, Georgiadis M, Kostoglou M, Panoskaltsis N, Pistikopoulos S, Mantalaris S, 2014, Development and experimental validation of a cyclin‐based population balance model of the cell cycle in leukemia cell lines, JOURNAL OF TISSUE ENGINEERING AND REGENERATIVE MEDICINE, Vol: 8, Pages: 489‐489, ISSN: 1932‐6254

6. Gamie Z, MacFarlane RJ, Tomkinson A, Moniakis A, Gui TT, Gamie Y, Mantalaris A, Tsiridis E, 2014, Skeletal tissue engineering using mesenchymal or embryonic stem cells: clinical and experimental data, EXPERT OPINION ON BIOLOGICAL THERAPY, Vol: 14, Pages: 1611‐1639, ISSN: 1471‐2598

7. Kiparissides A, Georgakis C, Mantalaris A, Pistikopoulos EN, 2014, Design of In Silico Experiments as a Tool for Nonlinear Sensitivity Analysis of Knowledge‐Driven Models, INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, Vol: 53, Pages: 7517‐7525, ISSN: 0888‐5885

8. Krieger A, Panoskaltsis N, Mantalaris A, Georgiadis MC, Pistikopoulos EN, 2014, Modeling and Analysis of Individualized Pharmacokinetics and Pharmacodynamics for Volatile Anesthesia, IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, Vol: 61, Pages: 25‐34, ISSN: 0018‐9294

9. Lee K‐Y, Buldum G, Mantalaris A, Bismarck A, 2014, More Than Meets the Eye in Bacterial Cellulose: Biosynthesis, Bioprocessing, and Applications in Advanced Fiber Composites, MACROMOLECULAR BIOSCIENCE, Vol: 14, Pages: 10‐32, ISSN: 1616‐5187

10. Marzinek JK, Bond PJ, Lian G, Zhao Y, Han L, Noro MG, Pistikopoulos EN, Mantalaris A, 2014, Free Energy Predictions of Ligand Binding to an alpha‐Helix Using Steered Molecular

Dynamics and Umbrella Sampling Simulations, JOURNAL OF CHEMICAL INFORMATION AND MODELING, Vol: 54, Pages: 2093‐2104, ISSN: 1549‐9596

11. Misener R, Chin J, Lai M, Gari MF, Velliou E, Panoskaltsis N, Pistikopoulos EN, Mantalaris A, 2014, Robust Superstructure Optimisation of a Bioreactor that Produces Red Blood Cells, 24th EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING, PTS A AND B, Vol: 33, Pages: 91‐96, ISSN: 1570‐7946

12. Misener R, Gari MF, Rende M, Velliou E, Panoskaltsis N, Pistikopoulos EN, Mantalaris A, 2014, Global superstructure optimisation of red blood cell production in a parallelised hollow fibre bioreactor, COMPUTERS & CHEMICAL ENGINEERING, Vol: 71, Pages: 532‐553, ISSN: 0098‐1354

13. Muenzer DGG, Kostoglou M, Georgiadis MC, Pistikopoulos EN, Mantalaris A, 2014, A Cyclin Distributed Cell Cycle Model in GS‐NS0, 24th EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING, PTS A AND B, Vol: 33, Pages: 19‐24, ISSN: 1570‐7946

14. Pefani E, Panoskaltsis N, Mantalaris A, Georgiadis MC, Pistikopoulos EN, 2014, Chemotherapy Drug Scheduling for the Induction Treatment of Patients With Acute Myeloid Leukemia, IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, Vol: 61, Pages: 2049‐2056, ISSN: 0018‐9294

15. Rende M, Panoskaltsis N, Morilla R, Mantalaris A, 2014, Novel successful cytokine‐free culture of acute leukemic cells in a perfused hollow‐fiber bioreactor, JOURNAL OF TISSUE ENGINEERING AND REGENERATIVE MEDICINE, Vol: 8, Pages: 48‐48, ISSN: 1932‐6254

16. Teo A, Mantalaris A, Lim M, 2014, Influence of culture pH on proliferation and cardiac differentiation of murine embryonic stem cells, BIOCHEMICAL ENGINEERING JOURNAL, Vol: 90, Pages: 8‐15, ISSN: 1369‐703X

17. Teo A, Mantalaris A, Song K, Lim M, 2014, A novel perfused rotary bioreactor for cardiomyogenesis of embryonic stem cells, BIOTECHNOLOGY LETTERS, Vol: 36, Pages: 947‐ 960, ISSN: 0141‐5492

18. Velliou E, Dos Santos SB, Gari MF, Misener R, Panoskaltsis N, Pistikopoulos E, Mantalaris A, 2014, Evolution of an AML model system under oxidative & starvation stress: a comparison between two and three dimensional cultures, JOURNAL OF TISSUE ENGINEERING AND REGENERATIVE MEDICINE, Vol: 8, Pages: 383‐383, ISSN: 1932‐6254

19. Velliou E, Fuentes‐Gari M, Misener R, Pefani E, Rende M, Panoskaltsis N, Mantalaris A, Pistikopoulos EN, 2014, A framework for the design, modeling and optimization of biomedical systems, PROCEEDINGS OF THE 8th INTERNATIONAL CONFERENCE ON FOUNDATIONS OF COMPUTER‐AIDED PROCESS DESIGN, Vol: 34, Pages: 225‐236, ISSN: 1570‐ 7946

20. Yeo DC, Wiraja C, Mantalaris AS, Xu C, 2014, Nanosensors for Regenerative Medicine, JOURNAL OF BIOMEDICAL NANOTECHNOLOGY, Vol: 10, Pages: 2722‐2746, ISSN: 1550‐7033

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21. Zavitsanou S, Mantalaris A, Georgiadis MC, Pistikopoulos EN, 2014, Optimization of Insulin Dosing in Patients with Type 1 Diabetes Mellitus, 24th EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING, PTS A AND B, Vol: 33, Pages: 1459‐1464, ISSN: 1570‐7946

22. Zhao Y, Marzinek JK, Bond PJ, Chen L, Li Q, Mantalaris A, Pistikopoulos EN, Noro MG, Han L, Lian G, 2014, A Study on Fe2+ ‐ alpha‐Helical‐Rich Keratin Complex Formation Using Isothermal Titration Calorimetry and Molecular Dynamics Simulation, JOURNAL OF PHARMACEUTICAL SCIENCES, Vol: 103, Pages: 1224‐1232, ISSN: 0022‐3549

Conference Contributions 1. Misener R, Allenby M, Gari MF, Rende M, Velliou E,

Panoskaltsis N, Pistikopoulos S, Mantalaris A, 2014, Optimisation under uncertainty for a bioreactor that produces red blood cells

Ruth Misener

Lecturer & Royal Academy of Engineering Research Fellow, Department of Computing, Imperial College London

Qualifications BSc in Chemical Engineering (Massachusetts Institute of Technology) PhD in Chemical Engineering (Princeton University)

Awards and DistinctionsRoyal Academy of Engineering Research Fellowship, 2012‐2017Imperial College Junior Research Fellowship (declined), 2012‐2015W. David Smith, Jr. Graduate Student Paper Award (2014)Best Paper of 2013; Journal of Global Optimization (awarded in 2014)Top Reviewer; Computers & Chemical Engineering, 2013Best Poster; 2nd Belgian Symposium on Tissue Engineering (BSTE), 2013USA National Science Foundation Graduate Research Fellowship, 2007‐2012 Princeton University Gordon Y. S. Wu Fellowship, 2007‐2012Robert C. Byrd Honors Scholarship, 2003‐2007Excellence in Teaching; Princeton School of Engineering & Applied Sciences, 2010 Member, MIT Tau Beta Pi‐Engineering Honor Society, 2007

Research InterestsResearch Domain: Optimisation Methods & Computation.Foundations: Global optimisation of mixed‐integer nonlinear programs (MINLP); Numerical optimisation algorithms; Computational optimisation frameworks; Implementations and software for global optimisation.Applications: Optimal chemotherapy scheduling for leukaemia; Bioprocess optimisation under uncertainty; Cell cycle modelling; Superstructure optimisation of chemical and petrochemical plants for energy efficiency; Process network design and operations.

Other ActivitiesSoftware development/maintenance of MINLP global optimization solvers ANTIGONE and GloMIQO.

Reviewer forADCHEM, AIChE Journal, Computational Optimization & Applications; Computers & Chemical Engineering (Top Reviewer, 2013; Top 10% in reviews completed, 2014 ‐ 2015); European Journal of Operational Research; Industrial & Engineering Chemistry Research; Journal of Global Optimization; Journal of Optimization Theory & Applications; Management Science; Mathematical Programming; Operations Research Letters; Optimization Letters.

Academic CollaborationsMIT, Texas A&M, University of Liége

Industrial CollaborationsGAMS Development Corp

PublicationsBook Chapters1. Fuentes‐Gari M., Misener R., Georgiadis M. C., Kostoglou M.,

Pistikopoulos E. N., Panoskaltsis N., Mantalaris A. Chemotherapy Optimization in Leukemia: Selecting the Right Mathematical Models for the Right Biological Processes. 9th IFAC Symposium on Biological & Medical Systems. Vol. 48 of IFAC‐ PapersOnLine. Berlin, DE; 2015; pp 534‐539.

2. Savvopoulos S. V., Misener R., Panoskaltsis N., Pistikopoulos E. N., Mantalaris A. Global Sensitivity Analysis for a Dynamic Model of Chronic Lymphocytic Leukemia Disease Trajectories. In Gernaey, Huusom, Gani (Eds), 12th International Symposium on Process Systems Engineering & 25th European Symposium on Computer Aided Process Engineering. Vol. 37 of Computer‐Aided Chemical Engineering. Copenhagen, DK; 2015; pp 185‐190.

3. Fuentes‐Gari M., Misener R., Pefani E., Garcia‐Munzer D., Kostoglou M., Georgiadis M. C., Panoskaltsis N., Pistikopoulos E. N., Mantalaris A. Cell cycle model selection for leukemia and its impact in chemotherapy outcomes. In Gernaey, Huusom, Gani (Eds), 12th International Symposium on Process Systems Engineering & 25th European Symposium on Computer Aided Process Engineering. Vol. 37 of Computer‐Aided Chemical Engineering. Copenhagen, DK; 2015; pp 2159‐2164.

4. Misener R., Chin J., Lai M., Fuentes‐Gari M., Velliou E., Panoskaltsis N., Pistikopoulos E. N., Mantalaris A. Robust Superstructure Optimisation of a Bioreactor that Produces

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Red Blood Cells. In Klemes, Varbanov, Liew (Ed.), 24th European Symposium on Computer Aided Process Engineering. Vol. 33 of Computer‐Aided Chemical Engineering. Budapest, Hungary; 2014; pp 91‐96

Journal Articles1. Fuentes‐Gari M., Misener R., Georgiadis M. C., Kostoglou M.,

Pistikopoulos E. N., Panoskaltsis N., Mantalaris A. Selecting a differential equation cell cycle model for simulating leukemia treatment; Industrial & Engineering Chemistry Research; 54:8847‐8859, 2015.

2. Velliou E., Brito dos Santos S., Papathanasiou M. M., Fuentes‐Gari M., Misener R., Panoskaltsis N., Mantalaris A., Pistikopoulos E. N. Towards unravelling the kinetics of an Acute Myeloid Leukaemia model system under oxidative and starvation stress: A comparison between two and three dimensional cultures; Bioprocess & Biosystems Engineering; 38:1589‐1600, 2015.

3. Fuentes‐Gari M., Velliou E., Misener R., Pefani E., Rende M., Panoskaltsis N., Mantalaris A., Pistikopoulos E. N. A systematic framework for the design, simulation and optimization of personalized healthcare: Making and healing blood; Computers & Chemical Engineering; 81:80‐93, 2015.

4. Fuentes‐Gari M., Misener R., Garcia‐Munzer D., Velliou E., Georgiadis M. C., Kostoglou M., Pistikopoulos E. N., Panoskaltsis N., Mantalaris A. A mathematical model of sub‐population kinetics for the deconvolution of leukaemia heterogeneity. Journal of The Royal Society Interface; 12(108), 2015.

5. Misener R., Smadbeck J. B., Floudas C. A. Dynamically‐generated cutting planes for mixed‐integer quadratically‐constrained quadratic programs and their incorporation into GloMIQO 2; Optimization Methods & Software; 30: 215‐249, 2015.

6. Velliou E., Brito dos Santos S., Fuentes‐Gari M., Misener R., Pefani E., Panoskaltsis N., Mantalaris A., Pistikopoulos E. N. Key environmental stress biomarker candidates for the optimisation of chemotherapy treatment of leukaemia; Malta Journal of Health Sciences; 1: 29‐34, 2014.

7. Misener R., Fuentes‐Gari M., Rende M., Velliou E., Panoskaltsis N., Pistikopoulos E. N., Mantalaris A., Global Superstructure Optimisation of Red Blood Cell Production in a Parallelised Hollow Fibre Bioreactor, Computers & Chemical Engineering; 71: 532‐553, 2014.

8. Misener R., Floudas C. A. ANTIGONE: Algorithms for coNTinuous / Integer Global Optimization of Nonlinear Equations, Journal of Global Optimization; 59: 503‐526, 2014.

9. Misener R., Floudas C. A. A framework for globally optimizing mixed‐integer signomial programs. Journal of Optimization Theory & Applications; 161: 905‐932, 2014.

Conference Contributions1. Mistry M., Misener R. Solving MINLP with Heat Exchangers:

Special Structure Detection and Large‐ Scale Global Optimisation. AIChE Annual Meeting. Salt Lake City, UT, 11/2015.

2. Allenby M. C., Tahlawi A., Brito Dos Santos S., Misener R., Hwang Y., Panoskaltsis N., Mantalaris A. Development of a hematopoietic microenvironment for the production of red

blood cells (RBCs) in a novel 3D hollow fibre bioreactor. TERMIS. Boston, MA, 09/2015.

3. Fuentes‐Gari M., Misener R., Georgiadis M. C., Kostoglou M., Pistikopoulos E. N., Panoskaltsis N., Mantalaris A. Chemotherapy Optimization in Leukemia: Selecting the Right Mathematical Models for the Right Biological Processes. 9th IFAC Symposium on Biological & Medical Systems. Berlin, DE; 09/2015

4. Misener R., Mistry M. Solving MINLP with Heat Exchangers: Special Structure Detection and Large‐ Scale Global Optimisation. 13th EUROPT Workshop on Advances in Continuous Optimisation, Edinburgh, Scotland; 07/2015.

5. Misener R., Fuentes‐Gari M., Allenby M. C., Panoskaltsis N., Pistikopoulos E. N., Mantalaris A. Stem Cell Bioprocessing under Uncertainty: A Case Study in Optimising Red Blood Cell Production. 17th British‐ French‐German Conference on Optimization. London, UK; 06/2015.

6. Savvopoulos S. V., Misener R., Panoskaltsis N., Pistikopoulos E. N., Mantalaris A. Global Sensitivity Analysis for a Dynamic Model of Chronic Lymphocytic Leukemia Disease Trajectories. 12th International Symposium on Process Systems Engineering & 25th European Symposium on Computer Aided Process Engineering. Copenhagen, DK; 06/2015.

7. Misener R., Fuentes‐Gari M., Velliou E., Panoskaltsis N., Pistikopoulos E. N., Mantalaris A. Ro‐ bust Design and Operation of Red Blood Cell Production in a Parallelised Hollow Fibre Bioreactor. AIChE Annual Meeting. Atlanta, GA; 11/2014.

8. Velliou E., Brito Dos Santos S., Fuentes‐Gari M., Misener R., Panoskaltsis N., Pistikopoulos E. N., Mantalaris A. Towards in vitro Optimization of Chemotherapy for Leukaemia Under Environ‐ mental Stress: Moving from Two to Three Dimensional Cultures. AIChE Annual Meeting. Atlanta, GA; 11/2014.

9. Fuentes‐Gari M., Misener R., Garcia‐Munzer D., Velliou E., Georgiadis M. C., Kostoglou M., Panoskaltsis N., Pistikopoulos E. N., Mantalaris A. Towards Personalized Treatments for Leukemia Based on Cell Cycle Heterogeneity: An Experimental/Modeling Approach. AIChE Annual Meeting. Atlanta, GA; 11/2014.

10. Misener R., Fuentes‐Gari M., Velliou E., Panoskaltsis N., Pistikopoulos E. N., Mantalaris A. Robust Design and Operation of Red Blood Cell Production in a Parallelised Hollow Fibre Bioreactor. INFORMS Annual Meeting. San Francisco, CA; 11/2014.

11. Velliou E., Fuentes‐Gari M., Misener R., Pefani E., Rende M., Panoskaltsis N., Pistikopoulos E. N., Mantalaris A. A framework for the design, modeling and optimization of biomedical systems. 8th International Conference on Foundations of Computer‐Aided Process Design. Cle Elum, WA; 07/2014.

12. Misener R., Chin J., Lai M., Fuentes‐Gari M., Velliou E., Panoskaltsis N., Pistikopoulos E. N., Mantalaris A. Robust Superstructure Optimisation of a Bioreactor that Produces Red Blood Cells. 24th European Symposium on Computer Aided Process Engineering. Budapest, Hungary; 06/2014.

Invited Lectures and Seminars1. Misener R. Mixed‐Integer Nonlinear Optimisation: Energy

Efficiency Applications. School of Mathematics; University of Edinburgh; Invited by Dr A Grothey and Prof K McKinnon; 10/2015.

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2. Ceccon F., Misener R. Detecting Pooling Network Structure. Short Research Announcement at the Oberwolfach MINLP Workshop, Oberwolfach, DE; 10/2015.

3. Misener R., Mistry M. Solving MINLP with Heat Exchangers: Special Structure Detection and Large‐ Scale Global Optimisation. 22nd International Symposium on Mathematical Programming, Pittsburgh, PA; Invited by Prof C Floudas; 07/2015.

4. Misener R. Global Optimisation; Centre for Process Systems Engineering Advanced Optimisation Course, Imperial College London, England; Invited by Prof C Adjiman; 04/2015.

5. Misener R. Stem Cell Bioprocessing under Uncertainty: A Case Study in Optimising Red Blood Cell Production. Centre for Computational Engineering Science; RWTH Aachen; Invited by Prof A Mitsos; 02/2015.

6. Misener R. Global Optimisation for Process Optimisation. Process Systems Enterprise; London, England; Invited by Dr P Kleniati; 01/2015.

7. Misener R. Deterministic Global Optimisation for Process Optimisation. Centre for Process Systems Engineering Annual Industrial Consortium Meeting, Imperial College London, England; Invited by Prof N Shah; 12/2014.

8. Misener R. Relating MINLP Model Formulations to Algorithmic Solution Strategies. Department of Electronics, Computer Sciences and Systems; University of Bologna; Invited by Prof A Lodi; 06/2014.

9. Misener R. Mixed‐Integer Nonlinear Optimization: Foundations and Applications. Department of Computing; Imperial College London; Job Talk; 03/2014.

10. Misener R. Making and Healing Blood: An Engineer’s Approach. Department of Chemical Engineering; University of Surrey, England; Invited by Prof K Kirkby; 01/2014.

Erich A. Müller

Professor of Thermodynamics, Department of Chemical Engineering, Imperial College London

Qualifications Ph.D. in Chemical Engineering, Cornell University (USA)M.Sc. in Chemical Engineering (honor mention), Universidad Simón Bolívar, (Venezuela)

Research InterestsMolecular simulation of complex fluids (liquid crystals, asphaltenes, polymers, etc.) adsorption and interfacial phenomena (activated carbons, nanotubes, colloids)Phase equilibria and thermophysical properties (VLE, supercritical fluids, etc.) bridging size scales from atomistic simulations to equation of state modelling (SAFT)Focus on application to engineering, environmental problems and high performance computing for engineering

Other ActivitiesFellow, Royal Society of Chemistry, 2011 Member, International Adsorption Society Senior Member, AIChE

Links with Other Academic BodiesVisiting Professor, Universidad de Concepcion Visiting Researcher, Cornell UniversityVisiting Researcher, North Carolina State University Visiting Researcher, Danmarks Techniske Højskole Visiting Researcher, Universidad de SevillaVisiting Professor, Universidad Pablo de Olavide

PublicationsJournal Articles1. Braga, Carlos, Amparo Galindo, and Erich A Müller.

“Nonequilibrium Molecular Dynamics Simulation of Diffusion at the Liquid‐Liquid Interface.” Journal of Chemical Physics 141, (2014): 154101. doi:10.1063/1.4897159.

2. Cumicheo, Constanza, Marcela Cartes, Hugo Segura, Erich A Müller, and Andrés Mejía. “High‐ Pressure Densities and Interfacial Tensions of Binary Systems Containing Carbon Dioxide+n‐Alkanes: (n‐Dodecane, n‐Tridecane, n‐Tetradecane).” Fluid Phase Equilibria 380 (2014): 82– 92. doi:10.1016/j.fluid.2014.07.039.

3. Forte, Esther, Andrew J. Haslam, George Jackson, and Erich A Müller. “Effective Coarse‐ Grained Solid‐Fluid Potentials and Their Application to Model Adsorption of Fluids on Heterogeneous Surfaces.” Physical Chemistry Chemical Physics 16 (2014): 19165–80. doi:10.1039/C4CP00670D.

4. Frentrup, Hendrik, Kyle Hart, Coray Colina, and Erich Muller. “In Silico Determination of Gas Permeabilities by Non‐Equilibrium Molecular Dynamics: CO2 and He Through PIM‐1.” Membranes 5, (2015): 99–119. doi:10.3390/membranes5010099.

5. Herdes, Carmelo, Erik E Santiso, Craig James, Julian Eastoe, and Erich A Müller. “Modelling the Interfacial Behaviour of Dilute Light‐Switching Surfactant Solutions.” Journal of Colloid and Interface Science 445, (2015): 16–23. doi:10.1016/j.jcis.2014.12.040.

6. Herdes, Carmelo, Tim S Totton, and Erich A Müller. “Coarse Grained Force Field for the Molecular Simulation of Natural Gases and Condensates.” Fluid Phase Equilibria 406 (2015): 91–100. doi:10.1016/j.fluid.2015.07.014.

7. Jover, Julio F, Erich A Müller, Andrew J. Haslam, Amparo Galindo, George Jackson, Hervé Toulhoat, and Carlos Nieto‐Draghi. “Aspects of Asphaltene Aggregation Obtained From Coarse‐Grained Molecular Modeling.” Energy and Fuels 29 (2015): 556–66. doi:10.1021/ef502209j.

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8. Jover, Julio, Amparo Galindo, George Jackson, Erich A Müller, and Andrew J. Haslam. “Fluid– Fluid Coexistence in an Athermal Colloid–Polymer Mixture: Thermodynamic Perturbation Theory and Continuum Molecular‐Dynamics Simulation.” Molecular Physics 113, (2015): 2608–28. doi:10.1080/00268976.2015.1047425.

9. Lau, Gabriel V, Ian J Ford, Patricia A Hunt, Erich A Müller, and George Jackson. “Surface Thermodynamics of Planar, Cylindrical, and Spherical Vapour‐Liquid Interfaces of Water.” Journal of Chemical Physics 142, (2015): 114701. doi:10.1063/1.4913371.

10. Lobanova, Olga, Carlos Avendaño, Thomas Lafitte, Erich A Müller, and George Jackson. “SAFT‐ Γ Force Field for the Simulation of Molecular Fluids: 4. a Single‐Site Coarse‐Grained Model of Water Applicable Over a Wide Temperature Range.” Molecular Physics 113, (2015): 1228–49. doi:10.1080/00268976.2015.1004804.

11. Mejía, Andrés, Marcela Cartes, Hugo Segura, and Erich A Müller. “Use of Equations of State and Coarse Grained Simulations to Complement Experiments: Describing the Interfacial Properties of Carbon Dioxide + Decane and Carbon Dioxide + Eicosane Mixtures.” Journal of Chemical and Engineering Data 59, (2014): 2928–41. doi:10.1021/je5000764.

12. Müller, E A, C Herdes, and T S Totton. Coarse‐Grained Models for Crude Oils: a Direct Link Between Equations of State and Molecular Simulations. OTC Brasil, Offshore Technology Conference, 2015. doi:10.4043/26155‐MS.

13. Müller, Erich A, and George Jackson. “Force‐Field Parameters From the SAFT‐Γ Equation of State for Use in Coarse‐Grained Molecular Simulations.” Annual Review of Chemical and Biomolecular Engineering 5, (2014): 405–27. doi:10.1146/annurev‐chembioeng‐061312‐ 103314.

14. Ramrattan, N S, C Avendaño, E A Müller, and A Galindo. “A Corresponding‐States Framework for the Description of the Mie Family of Intermolecular Potentials.” Molecular Physics 113, (2015): 932–47. doi:10.1080/00268976.2015.1025112.

15. Theodorakis, Panagiotis E, Erich A Müller, Richard V Craster, and O. K Matar. “Modelling the Superspreading of Surfactant‐Laden Droplets with Computer Simulation.” Soft Matter 11, (2015): 9254–61. doi:10.1039/C5SM02090E.

16. Theodorakis, Panagiotis E, Erich A Müller, Richard V Craster, and O. K Matar. “Insights Into Surfactant‐Assisted Superspreading.” Current Opinion in Colloid & Interface Science 19, (2014): 283–89. doi:10.1016/j.cocis.2014.04.007.

17. Theodorakis, Panagiotis E, Erich A Müller, Richard V Craster, and O. K Matar. “Superspreading: Mechanisms and Molecular Design.” Langmuir 31, (2015): 2304–9. doi:10.1021/la5044798.

18. Wu, Liang, Alexandr Malijevský, George Jackson, Erich A Müller, and Carlos Avendaño. “Orientational Ordering and Phase Behaviour of Binary Mixtures of Hard Spheres and Hard Spherocylinders.” Journal of Chemical Physics 143, (2015): 044906–14. doi:10.1063/1.4923291.

Costas C. Pantelides FREng

Professor of Chemical Engineering, Department of Chemical Engineering, Imperial College London

Qualifications BSc (Eng.) in Chemical Engineering (Imperial College London)MSc in Chemical Engineering (MIT)PhD, DIC in Symbolic & numerical solution methods (Imperial College London)

Awards and Distinctions2015 The Sargent Medal, The Institution of Chemical Engineers2015 The President’s Medal for Excellence in Innovation and Entrepreneurship, Imperial College London2010 Fellow of the Royal Academy of Engineering2009 Fellow of the Institution of Chemical Engineers2007 MacRobert Award of the Royal Academy of Engineering, awarded for the innovation of gPROMS 1998 Beilby Medal from the SCI, RSC and IoM for contributions to process systems engineering

Research InterestsProcess modelling methodologies & tools Systems‐based PharmaceuticsAb initio prediction of crystal structures

Other ActivitiesManaging Director, Process Systems Enterprise Ltd.

PublicationsJournal Articles1. Habgood M, Sugden IJ, Kazantsev AV, Adjiman CS,

Pantelides CC, 2015, Efficient Handling of Molecular Flexibility in Ab Initio Generation of Crystal Structures, JOURNAL OF CHEMICAL THEORY AND COMPUTATION, Vol: 11, Pages: 1957‐1969, ISSN: 1549‐9618

2. Vasileiadis M, Pantelides CC, Adjiman CS, 2015, Prediction of the crystal structures of axitinib, a polymorphic pharmaceutical molecule, CHEMICAL ENGINEERING SCIENCE, Vol: 121, Pages: 60‐76, ISSN: 0009‐2509

3. Pantelides CC, Adjiman CS, Kazantsev AV, 2014, General Computational Algorithms for Ab Initio Crystal Structure Prediction for Organic Molecules, PREDICTION AND

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CALCULATION OF CRYSTAL STRUCTURES: METHODS AND APPLICATIONS, Vol: 345, Pages: 25‐58, ISSN: 0340‐1022

Conference Contributions1. Rodriguez J, Andrade A, Lawal A, Samsatli N, Calado M,

Ramos A, Lafitte T, Fuentes J, Pantelides CC, 2014, An integrated framework for the dynamic modelling of solventbased CO2 capture processes, 12th International Conference on Greenhouse Gas Control Technologies, Energy Procedia, Vol: 63, Pages: 1206‐1217, ISSN: 1876‐6102

Lazaros G. Papageorgiou

Professor in Chemical Engineering, Department of Chemical Engineering, University College London

Qualifications Dipl. Eng. in Chemical Engineering (NTUA, Greece)PhD in Chemical Engineering (Imperial College London)

Research InterestsComputer‐aided process engineering, production planning andscheduling, supply-chain optimisation, mixed-integer optimisation

Other ActivitiesMember of IChemE CAPE Subject Group CommitteeMember of EPSRC Peer Review CollegeInternational Programme Committee member –ESCAPE21, ESCAPE22 Editorial board member of Current Opinion in Chemical Engineering Editorial board member of ISRN Chemical Engineering

Reviewer forIndustrial & Engineering Chemistry Research, Computers and Chemical Engineering, AIChE Journal, Chemical Engineering Research and Design, International Journal of Production Economics, European Journal of Operational Research, Computers and Industrial Engineering, Biotechnology Progress.

Academic CollaborationsImperial College London, King’s College London, University College London, Technical University of Crete, Aristotle University of Thessaloniki, National Technical University of Athens, University of Wisconsin, Instituto Superior Tecnico.

Industrial CollaborationsBayer, Syngenta, Unilever.

PublicationsJournal Articles1. Li, F. G. N., McDowall, W., Agnolucci, P., Akgul, O., &

Papageorgiou, L. G. (2015). Designing optimal infrastructures for delivering hydrogen to consumers. In R. B. Gupta, A. Basile, T. N. Veziroglu (Eds.),

2. Compendium of Hydrogen Energy, Volume 2: Hydrogen Storage, Distribution and Infrastructure. Woodhead Publishing.

3. Bennett, L., Kittas, A., Muirhead, G., Papageorgiou, L. G., & Tsoka, S. (2015). Detection of Composite Communities in Multiplex Biological Networks. SCIENTIFIC REPORTS, 5, ARTN 10345. doi:10.1038/srep10345

4. Liu, S., Simaria, A. S., Farid, S. S., & Papageorgiou, L. G. (2015). Mathematical programming approaches for downstream processing optimisation of biopharmaceuticals. CHEMICAL ENGINEERING RESEARCH AND DESIGN, 94, 18‐31. doi:10.1016/j.cherd.2014.12.002

5. Yang, L., Ainali, C., Kittas, A., Nestle, F. O., Papageorgiou, L. G., & Tsoka, S. (2015). Pathway‐level disease data mining through hyper‐box principles. MATHEMATICAL BIOSCIENCES, 260, 25‐34. doi:10.1016/j.mbs.2014.09.005

6. Calderon, A. J., Guerra, O. J., Papageorgiou, L. G., Siirola, J. J., & Reklaitis, G. V. (2015). Preliminary Evaluation of Shale Gas Reservoirs: Appraisal of Different Well‐Pad Designs via Performance Metrics. INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 54 (42), 10334‐10349. doi:10.1021/acs.iecr.5b01590

7. Yang, L., Liu, S., Tsoka, S., & Papageorgiou, L. G. (2015). Sample re‐weighting hyper box classifier for multi‐class data classification. COMPUTERS AND INDUSTRIAL ENGINEERING, 85, 44‐56. doi:10.1016/j.cie.2015.02.022

8. Akgul, O., Mac Dowell, N., Papageorgiou, L. G., & Shah, N. (2014). A mixed integer nonlinear programming (MINLP) supply chain optimisation framework for carbon negative electricity generation using biomass to energy with CCS (BECCS) in the UK. INTERNATIONAL JOURNAL OF GREENHOUSE GAS CONTROL, 28, 189‐202. doi:10.1016/j.ijggc.2014.06.017

9. Liu, S., Simaria, A. S., Farid, S. S., & Papageorgiou, L. G. (2014). An Optimisation‐based approach for biopharmaceutical manufacturing. COMPUTER AIDED CHEMICAL ENGINEERING, 33, 1183‐1188. doi:10.1016/B978‐0‐444‐63455‐9.50032‐5

10. Siganporia, C. C., Ghosh, S., Daszkowski, T., Papageorgiou, L. G., & Farid, S. S. (2014). Capacity planning for batch and perfusion bioprocesses across multiple biopharmaceutical facilities. BIOTECHNOLOGY PROGRESS, 30 (3), 594‐606. doi:10.1002/btpr.1860

11. Bennett, L., Kittas, A., Liu, S., Papageorgiou, L. G., & Tsoka, S. (2014). Community Structure Detection for Overlapping Modules through Mathematical Programming in Protein Interaction Networks. PLOS ONE, 9 (11), ARTN e112821. doi:10.1371/journal.pone.0112821

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12. Zhang, D., Liu, S., & Papageorgiou, L. G. (2014). Fair cost distribution among smart homes with microgrid. ENERGY CONVERSION AND MANAGEMENT, 80, 498‐508. doi:10.1016/j.enconman.2014.01.012

13. Zhang, D., Evangelisti, S., Lettieri, P., & Papageorgiou, L. G. (2014). Optimal design of CHP‐based microgrids: Multiobjective optimisation and life cycle assessment. ENERGY, 85, 181–193, doi:10.1016/j.energy.2015.03.036

14. Liu, S., Yahia, A., & Papageorgiou, L. G. (2014). Optimal Production and Maintenance Planning of Biopharmaceutical Manufacturing under Performance Decay. INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 53 (44), 17075‐17091. doi:10.1021/ie5008807

15. Akgul, O. (2014). Optimisation of Bioenergy Supply Chains (Doctoral dissertation). UCL.

16. Liu, S., Simaria, A. S., Farid, S. S., & Papageorgiou, L. G. (2014). Optimising chromatography strategies of antibody purification processes by mixed integer fractional programming techniques. COMPUTERS AND CHEMICAL ENGINEERING, 68, 151‐164. doi:10.1016/j.compchemeng.2014.05.005

17. Yang, L., Ainali, C., Tsoka, S., & Papageorgiou, L. G. (2014). Pathway activity inference for multiclass disease classification through a mathematical programming optimisation framework. BMC Bioinformatics, 15, 390‐?. doi:10.1186/s12859‐014‐0390‐2

18. Al‐Salem, S. M., Papageorgiou, L. G., & Lettieri, P. (2014). Techno‐economic assessment of thermo‐ chemical treatment (TCT) units in the Greater London area. CHEMICAL ENGINEERING JOURNAL, 248, 253‐263. doi:10.1016/j.cej.2014.03.053

Panos Parpas

Senior Lecturer, Department of Computing, Imperial College London

Qualifications PhD in Computer Science, Imperial College London (2006) MSc in Computer Science, Imperial College London (2002)

Awards and DistinctionsMIT CIY Fellowship

Research InterestsDevelopment and analysis of algorithms for large scale optimisation problems

Other ActivitiesAthena‐Swan representative for the Department of Computing

Reviewer forAutomatica, Computational and Applied Mathematics, Computational Management Science, Computational Optimization and Applications, Computational Statistics and Data Analysis, Computers and Operations Research, European Journal of Operational Research, IMA Journal of ManagementMathematics, Information Processing Letters, INFORMS Journal on Computing, International Review of Economics and Finance, Journal of Computational Finance, Journal of Global Optimization, Journal of the Operational Research Society, Kybernetika, Management Science, Mathematics of Operations Research, Mathematical Programming, Operations Research, Optimization Methods and Software, Quantitative Finance, SIAM Journal on Control and Optimization.

Academic CollaborationsMIT Engineering Systems DivisionDepartment of Statistical Science Duke University Department of Mathematics EdinburghSchool of Pharmacy Nottingham

Industrial CollaborationsIBM

PublicationsJournal Articles1. Wright, R., Abraham, E., Parpas, P., and Stoianov, I. Control of

Water Distribution Networks with Dynamic DMA Topology using Strictly Feasible Sequential Convex Programming, Journal of Water Resources Research, 2015.

2. P. Parpas, B. Ustun, M. Webster and Q.K. Tran. Importance Sampling in Stochastic Programming with MCMC, INFORMS Journal on Computing, Published Online: April 24, 2015, Page Range: 358 ‐ 377

3. C.P Ho, P. Parpas. Singularly Perturbed Markov Decision Processes: A Multiresolution Algorithm, SIAM Journal on Control and Optimization, 52(6), 3854‐3886, 2014.

4. R. Wright, I. Stoianov, P. Parpas, K. Henderson, J. King. Adaptive Water Distribution Networks with Dynamically Reconfigurable Topology, Journal of Hydroinformatics, November 2014, 16 (6) 1280‐1301.

5. P. Parpas, and M. Webster. A stochastic multiscale model for electricity generation capacity expansion, European Journal of Operational Research, Volume 232, Issue 2, Pages 359‐374, January 2014.

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Berc Rustem

Professor of Computational Methods in Operations Research, Department of Computing, ImperialCollege London

Qualifications B.S. MSc, PhD, FIMA, CMath

Awards and DistinctionsPresident of Society of Computational Economics, 2002‐04Special issue of Computational Economics in honour of Berc Rustem (V. 27, Nos 2‐3, 2006)Special issue of Computational Management Science in honour of Berc Rustem (V. 11, No. 3, 2014)

Research InterestsOptimisation Algorithms, Decision and Design Under Uncertainty, Worst‐Case Design, Stochastic Optimisation

Other ActivitiesPast Managing Editor: Journal of Economic Dynamics & Control: 1987‐2002.

Academic CollaborationsUniversity of Warwick; University of Florida

Industrial CollaborationsCommerzbank; BAe Systems

EditorAutomatica (2003‐2015)Computational Management Science (2002‐2012)

Editorial Advisory BoardJournal of Economic Dynamics & Control

Associate EditorRoyal Society Proceedings (Series A; 2008‐14)Computational EconomicsJournal of Global OptimizationOptimization LettersComputational Science & Engineering

Book Series EditorAdvances in Computational Management ScienceAdvances in Computational Economics

Organiser & Programme Committee Co-chair17th British‐French‐German Conference on Optimization,15‐17June 2015, London, http://optimisation.doc.ic.ac.uk/bfg2015/

ActivitiesAssociate Director ‐ Research ‐ Centre for Process Systems Engineering, Imperial College

PublicationsJournal Articles1. Kapsos M, Christofides N, Rustem B, 2014, Worst‐case

robust Omega ratio, European Journal of Operational Research, Vol:234, Pages:499‐507

2. Kakouris I, Rustem B, 2014, Robust portfolio optimization with copulas, European Journal of Operational Research, Vol:235, Pages:28‐37

3. Kapsos M, Zymler S, Christofides N, et al., 2014, Optimizing the Omega ratio using linear programming, Journal of Computational Finance, Vol:17, Pages:49‐57

Eva Sørensen

Professor of Chemical Engineering, Department of Chemical Engineering, University College LondonDeputy Head of Department (Education)

Qualifications MSc in Chemical Engineering (NTNU, Norway)PhD in Chemical Engineering (NTNU, Norway)MA in Education (University College London)Chartered Engineer (CEng)Chartered Scientist (CSci)

Awards and DistinctionsFellow of the Institution of Chemical Engineers (IChemE)Fellow of the Higher Education Academy (HEA)IChemE Sustainability Teaching Award (2015)ExxonMobil Award for Excellence in TeachingRoyal Academy of Engineering (2013)

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Royal Academy of Engineering Secondment Award (2005)Faculty Teaching Award for Outstanding Achievements in Teaching Faculty of Engineering,University College London, UK (2001)Postdoctoral Research Scholarship, Norwegian Research Foundation (1995‐1996)Research Scholarship, Norwegian Research Foundation (1993‐1994)University Scholarship, NTNU, Norway (1990‐1993)

SecondmentsBP Refining Technology (2005)

Research InterestsSystematic methodologies for mathematical modelling of fluid separation processes, in particular, distillation, membrane separation, chromatography and hybrids thereofOptimal design and operation of fluid separation processesMicro‐scale separation processesOptimal separation process selectionOptimal process design, operation and controlEducation

Other ActivitiesEditor‐in‐Chief of Chemical Engineering Research & DesignMember of the European Federation of Chemical Engineers (EFCE) Executive BoardMember of EFCE’s Working Party on Fluid SeparationsMember of IChemE’s Education & Accreditation BoardMember of Engineering Council’s Engineering Accreditation BoardMember of IChemE’s Education Special Interest Group CommitteeMember of IChemE’s Fluid Separations Special Interest Group CommitteeMember of American Institute of Chemical Engineers (AIChE)Member of European Society for Engineering Education (SEFI)Member of EFSRC Peer Review CollegeEditorial Board Member of Chemical Engineering & TechnologyChair of Organising Committee for Distillation & Absorption Conference, 2006

Reviewer forDeutsche Forschungsgemeinschaft (DFG)Dutch Technology Foundation (STW)CONICYT ChileAIChE JournalBiomass and BioenergyChemical Engineering & ProcessingChemical Engineering & TechnologyChemical Engineering ScienceComputers and Chemical EngineeringJournal of Membrane ScienceJournal of the Science of Food and AgricultureJournal of European Engineering Education

Academic CollaborationsUniversity College London, Department of Biochemical EngineeringImperial College London, Department of Chemical EngineeringDortmund University, Germany

Industrial CollaborationsBioMarin, Eli Lilly

PublicationsJournal Articles1. Akinmolayan, F., Thornhill, N., & Sorensen, E. (2015). A

Detailed Mathematical Modelling Representation of Clean Water Treatment Plants. 12TH INTERNATIONAL SYMPOSIUM ON PROCESS SYSTEMS ENGINEERING AND 25th EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING, PT C, 37, 2537‐2542.

2. Patel, N., Bracewell, D., & Sorensen, E. (2015). Dynamic Simulation of a Batch Aqueous Two‐Phase Extraction Process for α‐Amylase. COMPUTER AIDED CHEMICAL ENGINEERING, 37, 713‐718. doi:10.1016/B978‐0‐444‐63578‐5.50114‐6

3. Triana, C. F., Fraga, E. S., & Sorensen, E. (2015). Energy assessment of different configurations for the ethanol production process from lignocellulosic biomass. COMPUTER AIDED CHEMICAL ENGINEERING, 37, 2285‐2290. doi:10.1016/B978‐0‐444‐63576‐1.50075‐3

4. Brunazzi, E., Repke, J. ‐. U., & Sorensen, E. (2015). Special Issue Distillation and Absorption. CHEMICAL ENGINEERING RESEARCH & DESIGN, 99, 1. doi:10.1016/j.cherd.2015.06.006

5. Close, E. J., Salm, J. R., Bracewell, D. G., & Sorensen, E. (2014). A model based approach for identifying robust operating conditions for industrial chromatography with process variability. CHEMICAL ENGINEERING SCIENCE, 116, 284‐295. doi:10.1016/j.ces.2014.03.010

6. Manage, M. N., Sorensen, E., Simons, S., & Brett, D. J. L. (2014). A modelling approach to assessing the feasibility of the integration of power stations with steam electrolysers. CHEMICAL ENGINEERING RESEARCH AND DESIGN, 37, 2285-2290. doi:10.1016/j.cherd.2014.07.015

7. Ng, C. K. S., Rousset, F., Valery, E., Bracewell, D. G., & Sorensen, E. (2014). Design of high productivity sequential multi‐column chromatography for antibody capture. FOOD AND BIOPRODUCTS PROCESSING, 92 (C2), 233‐241. doi:10.1016/j.fbp.2013.10.003

8. Close, E., Salm, J., Sorensen, E., & Bracewell, D. G. (2014). Minimalist approach to mechanistic modelling of chromatography for intermediate purification and polishing steps. ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 247.

9. Close, E. J., Salm, J. R., Bracewell, D. G., & Sorensen, E. (2014). Modelling of industrial biopharmaceutical multicomponent chromatography. CHEMICAL ENGINEERING RESEARCH & DESIGN, 92 (7), 1304‐ 1314. doi:10.1016/j.cherd.2013.10.022

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Michail Stamatakis

Lecturer in Chemical Engineering, Department of Chemical Engineering, University College London

Qualifications MEng in Chemical Engineering (NTUA, Greece)PhD in Chemical and Biomolecular Engineering (Rice University, USA)

Awards and Distinctions2015 ‐ Shortlisted for IChemE Global Awards – Research Project of the Year2013 ‐ Top Reviewer, Computers & Chemical Engineering2007 ‐ Outstanding Teaching, Department of Chemical and Biomolecular Engineering, Rice University2007 ‐ Kobayashi Fellowship, Department of Chemical and Biomolecular Engineering, Rice University

Research InterestsFirst‐principles based chemical process modelling toolsComputational catalyst engineering

Reviewer forACS Catalysis, ACS Nano, AIChE Journal, Biofabrication, Biophysical Journal, BMC Bioinformatics, Catalysis Science & Technology, Chemical Engineering and Processing: Process Intensification, Chemical Engineering Journal, Chemical EngineeringResearch and Design, Computers & Chemical Engineering, Industrial & Engineering Chemistry Research, Journal of Chemical Physics, Journal of Mathematical Biology, Journal of Molecular Liquids, Journal of Multiscale Modeling & Simulation(SIAM), Journal of Physical Chemistry, Physical Review E, Physical Review Letters, PLoS One, Science Advances, Surface Science.

Academic CollaborationsThomas Young Centre, UK Catalysis Hub, University College London, Oxford University, University of Pittsburgh, University of Wisconsin at Madison, Tufts University, Integrated Mesoscale Architectures for Sustainable Catalysis – Energy, Frontier ResearchCentre, Harvard University.

PublicationsJournal Articles1. M. Stamatakis. (2015). “Kinetic Modelling of Heterogeneous

Catalytic Systems”. Journal of Physics: Condensed Matter 27: 013001. [Invited review article]

2. Nikbin, N., Austin, N., Vlachos, D. G., Stamatakis, M. and G. Mpourmpakis (2015). “Catalysis at the Sub‐ Nanoscale: Complex CO Oxidation Chemistry on a Few Au Atoms”. Catalysis Science & Technology 5(1): 134‐141. [Featured on the cover of the issue].

3. Piccinin, S. and M. Stamatakis (2014). “CO Oxidation on Pd(111): A First‐Principles Based Kinetic Monte Carlo Study”. ACS Catalysis 4: 2143‐2152.

4. Herrmann, S., Stamatakis, M., Andriotis, A. N. and G. Mpourmpakis (2014). “Adsorption Behavior of Noble Metal Clusters and Their Alloys”. Journal of Computational and Theoretical Nanoscience 11(2): 511‐520.

Conference Contributions1. Piccinin, S. and M. Stamatakis. “Rationalising the Relation

Between Adlayer Structure and Observed Kinetics in CO Oxidation on Pd(111)”. American Institute of Chemical Engineers Annual Meeting, Salt Lake, UT, USA. Nov 10, 2015.

2. Nikbin, N., Austin, N., Christiansen, M., Vlachos, D. G., Stamatakis, M. and G. Mpourmpakis. “Unravelling the Complexity of CO Oxidation Catalysis on Au Nanoclusters”. Short oral presentation within the Discussion symposium 6 ‐ “Oxidation Catalysis ‐ Pollution control”, XII European Congress on Catalysis (EuropaCatXII), Kazan, Russia. Sep 2, 2015.

3. Piccinin, S. and M. Stamatakis. “Coverage Effects for the CO Oxidation Reaction on O‐Rich Pd(111)”. Inaugural UK Catalysis Conference, Loughborough, UK. Jan 9, 2015.

4. Piccinin, S. and M. Stamatakis. “CO Oxidation on O‐Rich Pd(111): How Does Adlayer Structure Affect Reactivity?”. American Institute of Chemical Engineers Annual Meeting, Atlanta, GA, USA. Nov 17, 2014.

Invited Lectures and Seminars1. Stamatakis, M., Michaelides, A. and E. C. H. Sykes “Catalysis

on Single Atom Alloys: Theoretical Investigations and Opportunities”. Energy Frontier Research Center “Integrated Mesoscale Architectures for Sustainable Catalysis”, Harvard University, Boston, USA, Oct 16. 2015. [Invited seminar via teleconference]

2. M. Stamatakis. “Unravelling the Complexity of Catalytic Kinetics: Computational Method Development, Applications and Perspective”. Institute of Energy and Process Systems Engineering, Technische Universität Braunschweig, Germany, Mar 9, 2015.

3. M. Stamatakis. “Elucidating the Catalytic Activity of Transition Metal Surfaces via First‐Principles Kinetic Modelling: Method Development and Applications”. International Max Planck Research School Functional Interfaces in Physics and Chemistry, Workshop “Micro to Macro”, Schloss Ringberg, Kreuth, Germany, Feb 12, 2015.

4. M. Stamatakis. “Pushing the Frontiers of Ab Initio Kinetic Simulations in Heterogeneous Catalysis”. Centre Blaise Pascal, École Normale Supérieure de Lyon, France. Oct 24, 2014.

5. M. Stamatakis. “Unravelling the complexity of catalytic kinetics: computational method development, applications and perspective”. Chemical Engineering Department, University of Newcastle, UK. Oct 21, 2014.

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6. M. Stamatakis. “Pushing the Frontiers of Ab Initio Kinetic Simulations in Heterogeneous Catalysis”. Workshop: From the Chemical Bond to the Chemical Plant: Computational and Materials Challenges in Gas Conversion Technologies, International Centre for Materials Science, Jawaharlal Nehru Centre for Advanced Scientific Research, Jakkur, Bangalore, India. Aug 25, 2014.

7. M. Stamatakis. “From Fundamental Understanding to Catalyst Design: Pushing the Frontiers of First‐Principles Kinetic Simulation in Catalysis”. Workshop on International Research and Education on Computational Materials Design in Asia, Department of Applied Physics, Osaka University, Osaka, Japan. Jun 3, 2014.

8. M. Stamatakis. “Structure Sensitive or Not? The Effect of Catalytic Surface Morphology on H2 Production via the Water‐Gas Shift Reaction”. JSPS Core‐to‐Core Program: A. Advanced Research Networks ‐ International Workshop of Computational Nano‐Materials Design on Green Energy, Toyonaka Campus, Osaka University, Osaka, Japan. Jun 2, 2014.

Nina F. Thornhill FREng

Professor of Process Automation, Department of Chemical Engineering, Imperial College London, Holder of ABB/Royal Academy of Engineering Research Chair in Process Automation

QualificationsBA in Physics (Oxford University)MSc in Control Systems (Imperial College)PhD (UCL)

Awards and DistinctionsFellow of the Royal Academy of EngineeringFellow of the IChemEFellow of the IET

SecondmentsMarie Curie Fellowship secondment to ABB Corporate Research, Poland, 2012 and 2013Royal Academy of Engineering Global Research Award with ABB Corporate Research, Norway, April‐September 2005Royal Academy of Engineering Foresight Award with University of Alberta, Canada, January‐September 2001Royal Society Industry Fellowship with BP International, 1992‐5

Research interestsIndustrial data analysis using time series analysis and signal processing; Plant‐wide performance assessment; Applications in oil and gas, chemicals, bioprocesses and electricity supply.

Other ActivitiesIChemE: Chair of Process Management & Control Subject GroupAssociate Editor of Control Engineering Practice 2006‐2013

Reviewer forAutomaticaBiotechnology and BioengineeringChemical Engineering Research and DesignComputers & Chemical EngineeringControl Engineering PracticeIEEE Transactions on Control System TechnologyIndustrial and Engineering Chemistry ResearchJournal of Process Control

Academic CollaborationsHelmut Schmidt University, Hamburg, Institut für AutomatisierungstechnikImperial College London, Department of Electrical and Electronic EngineeringImperial College London, Department of Mechanical EngineeringNorwegian University of Science and Technology – NTNU TrondheimUniversity of Alberta, Department of Chemical and Materials University College London, Department of Biochemical Engineering

Industrial collaborationsABB Corporate ResearchABB Strategic R&D for Oil, Gas and PetrochemicalsESD Training SimulationBASFBP Exploration and ProductionFingrid OyjNational GridStatnett SF

PublicationsJournal Articles1. Cicciotti, M., Xenos, P.D., Bouaswaig, A.E.F., Thornhill, N.F.

and Martinez‐Botas, R.F., 2015, Physical modelling of industrial multistage centrifugal compressors for monitoring and simulation, Journal of Mechanical Engineering Science, 229, 3433‐3448.

2. Barocio, E., Pal, B.C., Thornhill, N.F., and Messina A.R., 2015, A dynamic mode decomposition framework for global power system oscillation analysis, IEEE Transactions on Power Systems, 30, 2902‐2912.

3. Cecilio, I., Ottewill, J.R., Fretheim, H., and Thornhill, N.F., 2015, Multivariate detection of transient disturbances for uni‐ and multi‐rate systems, IEEE Transactions on Control Systems Technology, 23, 1477‐1493, http://dx.doi.org/10.1109/TCST.2014.2377182

4. Kopanos, G.M., Xenos, P.D., Cicciotti, M., Pistikopoulos, E.N and Thornhill, N.F., 2015, Operational and maintenance

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planning in networks of compressors in parallel: the air separation plant case, Applied Energy, 146, 453‐470 http://dx.doi.org/10.1016/j.apenergy.2015.01.080

5. Xenos, D.P., Cicciotti, M., Kopanos, G.M., Bouaswaig, A.E.F., Kahrs, O., Martinez‐Botas, R.F., and Thornhill, N.F., 2015, Optimization of compressors in parallel: Real Time Optimization (RTO) of compressors in chemical plants ‐ An industrial case study, Applied Energy, 144, 51‐63.

6. Cecilio, I., Ottewill, J., Pretlove, J., and Thornhill, N.F., 2014, Nearest neighbors method for detecting transient disturbances in process and electromechanical systems, Journal of Process Control, 24, 1382‐1393.

7. Cecilio, I., Ottewill, J.R., Pretlove, J., and Thornhill, N.F., 2014, Nearest neighbors method for detecting transient disturbances in process and electromechanical systems, Journal of Process Control, 24, 1382‐1393.

8. Ikram, W., Petersen, S., Orten, P., and Thornhill, N.F., 2014, Adaptive multi‐channel transmission power control for industrial wireless instrumentation, IEEE Transactions on Industrial Informatics, 10, 978‐990.

9. Yang, Y., Farid, S.S., Thornhill, N.F., 2014, Data mining in rapid prediction and debottlenecking of biomanufacturing facilities, Journal of Biotechnology, 179, 17‐25.

Conference Presentations1. Cecilio, I.M., Ottewill, J.R., and Thornhill, N.F., 2015, Adapting

nearest neighbors‐based monitoring methods to irregularly sampled measurements, Annual Conference of the PHM Society 2015, San Diego, California, USA, Oct 19‐24.

2. Budinis, S., and Thornhill, N.F., 2015, 2015, Control of centrifugal compressors via model predictive control for enhanced oil recovery applications. 2nd IFAC Workshop on Automatic Control in Offshore Oil and Gas Production OOGP 2015 — Florianópolis, Brazil, 27–29 May 2015, IFAC‐PapersOnLine, 48(6), 9‐14.

3. Leng, D., and Thornhill, N.F., 2015, Process disturbance cause & effect analysis using Bayesian networks, 9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes SAFEPROCESS 2015 — Paris, 2–4 September 2015, IFAC PapersOnLine, 48(21), 1457‐1464.

4. Cecilio, I.M., Ottewill, J.R., and Thornhill, N.F., 2015, Determining the propagation path of a disturbance in multi‐rate systems, 9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes SAFEPROCESS 2015 — Paris, 2–4 September 2015, IFAC PapersOnLine, 48(21), 784‐789.

5. Mohd Noor, I., Fretheim, H., Thorud, E., and Thornhill, N.F., 2015, Quantifying the demand‐side response capability of industrial plants to participate in power system frequency control schemes, IEEE PowerTech Eindhoven, June 29‐July 2nd 2015.

6. Mechleri, E.D., Mac Dowell, N., and Thornhill, N.F., Model predictive control of post‐combustion CO2 capture process integrated with a gas‐fired power plant, Computer Aided Chemical Engineering (Proceedings of ESCAPE 25), 37, 161‐166, 2015.

7. Budinis, S., and Thornhill, N.F., 2015, Supercritical gas recycle analysis for surge control of centrifugal compressors, Computer Aided Chemical Engineering (Proceedings of

ESCAPE 25), 37, 1583‐1588, 2015.8. Romero, D.D., Graven, T‐G., and Thornhill, N.F., 2015, Linking

process, electrical and logical connectivity for supported fault diagnosis, Computer Aided Chemical Engineering (Proceedings of ESCAPE 25), 37, 965‐970, 2015.

9. Yang, Y., Velayudhan, A., Thornhill, N.F., and Farid, S.S., 2015, Manufacturability indices for highconcentration monoclonal antibody formulations, Computer Aided Chemical Engineering (Proceedings of ESCAPE 25), 37, 2147‐2152, 2015.

10. Akinmolayan, F., Thornhill, N.F., Sorensen., E., 2015, A detailed mathematical modelling representation of clean water treatment plants, Computer Aided Chemical Engineering (Proceedings of ESCAPE 25), 37, 2537‐2542, 2015.

11. Xenos, D.P., Lunde, E., and Thornhill, N.F., 2015, Optimal operation and maintenance of gas compressor stations: an integrated framework applied to a large‐scale industrial case, ASME Turbo Expo 2015, June 16‐20 2014, Montreal, Canada, June 15‐19, 2015.

12. Zhang, Y., Larsson, M., Pal, B.C., and Thornhill, N.F., 2015, Simulation approach to reliability analysis of WAMPAC system, Presented at IEEE PES ISGT 2015, Washington DC, Feb 17‐20 2015.

13. Romero, D.D., Gravel, T‐G and Thornhill, N.F., 2014, Towards the development of a tool for visualising plantwide dependencies, 19th IEEE International Conference on Emerging Technologies and Factory Automation, Sept 16‐19th 2014, Barcelona, Spain.

14. Romero, D.D., and Thornhill, N.F., 2014, Integration, navigation and exploration of plant topology networks using the property‐graph model, 2014 IEEE/SICE International Symposium on System Integration, Tokyo, Japan, December 15‐17, 2014. Paper SuP2C.2, pp743‐748.

15. Ikram, W., Jansson, N., Harvei, T., Aakvaag, N., Halvorsen, I., Petersen, S., Carlsen, S., and Thornhill, N.F., 2014, Wireless communication in process control loop: Requirements analysis, industry practices and experimental evaluation, IEEE EFTA Conference, Barcelona, Spain, September 16th‐19th 2014.

16. Arroyo, E., Schulze, D., Christiansen, L., Fay, A., and Thornhill, N.F., 2014, Derivation of diagnostic models based on formalized process knowledge, IFAC World Congress, August 24‐29, 2014, Cape Town, South Africa, pp 3456‐3464.

17. Dionysios P. Xenos, Nina F. Thornhill, Matteo Cicciotti, Ala E.F. Bouaswaig, 2014, Preprocessing of raw data for developing steady‐state data‐driven models for optimizing compressor stations, UKACC 10th International Conference on Control, Loughborough, 9‐11 July 2014, 438‐443.

18. Budinis, S., and Thornhill, N.F., 2014, An integrated control technique foe compressor operation, UKACC 10th International Conference on Control, Loughborough, 9‐11 July 2014. 444‐449.

19. Ersdal A.E., Fabozzi, D., Imsland, L., and Thornhill, N.F., 2014, Model predictive control for power system frequency control. taking into account imbalance uncertainty, IFAC World Congress, August 24‐29, 2014, Cape Town, South Africa, pp 981‐986.

20. Xenos, D.P., Cicciotti, M., Bouaswaig, A.E.F., Thornhill,. N.F., and Martinez‐Botas, R.F., 2014, Modeling and optimization of industrial centrifugal compressor stations employing data‐driven methods, ASME Turbo Expo 2014, June 16‐20 2014, Düsseldorf, Germany.

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21. Cicciotti, M., Xenos, D.P., Martinez‐Botas, R.F., Thornhill,. N.F., 2014, Performance monitoring of centrifugal industrial compressors using meanline modelling and recursive least‐squares, ASME Turbo Expo 2014, June 16‐20 2014, Düsseldorf, Germany.

22. Cicciotti, M., Xenos, D.P., Bouaswaig, A.E.F., Martinez‐Botas, R.F., Manenti, F., Thornhill,. N.F., and Bouaswaig, A.E.F., 2014, Simultaneous nonlinear reconciliation and update of parameters for online use of first‐principle models: An industrial case‐study on compressors, 24th European Conference on Computer Aided Process Engineering (ESCAPE 24).

23. Xenos, D.P., Kopanos, G.M., Cicciotti, M., Pistikopoulos, E.S., and Thornhill,. N.F., 2014, Operational optimization of compressors in parallel considering condition‐based maintenance, 24th European Conference on Computer Aided Process Engineering (ESCAPE 24).

24. Mechleri, E.D., Biliyok, C., and Thornhill, N.F., 2014, Dynamic simulation of post‐combustion CO2 capture with MEA in a gas based power plant, 24th European Conference on Computer Aided Process Engineering (ESCAPE 24).

25. Romero, D., Thornhill, N.F., and Graven, T‐G., 2014, Investigations on information‐rich visualizations to explore process connectivity and causality, 24th European Conference on Computer Aided Process Engineering (ESCAPE 24).

Wolfram Wiesemann

Associate Professor of Management Science and Operations; Fellow of the KPMG Centre for Advanced Business Analytics, Imperial College London

QualificationsMSc in Management and Computing at Darmstadt University of Technology (2006)PhD in Operations Research at Imperial College London (2010)

Research InterestsDr Wolfram Wiesemann’s research focuses on the development of tractable computational methods for the solution of stochastic and robust optimisation problems, as well as, applications in operations management, finance and health care.

Reviewer forAnnals of Operations Research, Applied Mathematical Modelling,

Asia‐Pacific Journal of Operational Research, Automatica, Computational Management Science, The Computer Journal, Computers & Chemical Engineering, Energy Systems, European Journal of Operational Research, IIE Transactions, Journal of Global Optimization, Journal of Network and Systems Management, Management Science, Mathematical Programming, Mathematics of Operations Research, Operations Research, Operations Research Letters, Optimization and Engineering, Optimization Letters, SIAM Journal on Optimization, Transportation Science, as well as, the IFAC Conference on Manufacturing, Modelling, Management and Control.

Academic CollaborationsCarnegie Mellon UniversityColumbia UniversityNational University of SingaporePrinceton University

PublicationsJournal Articles1. Hanasusanto GA, Kuhn D, Wiesemann W, 2015, K-Adaptability

in Two-Stage Robust Binary Programming, Operations Research, Vol: 63, Pages: 877-891, ISSN: 0030-364X

2. Hanasusanto GA, Kuhn D, Wiesemann W, 2015, K-Adaptability in Distributionally Robust Binary Programming, Operations Research Letters, Vol: 44, Pages: 6-11, ISSN: 0167-6377

3. Hanasusanto GA, Roitch V, Kuhn D, Wiesemann W, 2015, A distributionally robust perspective on uncertainty quantification and chance constrained programming, Mathematical Programming, Vol: 151, Pages: 35-62, ISSN: 0025-5610

4. Hanasusanto GA, Kuhn, D, Wiesemann, W, 2015, A Comment on “Computational Complexity of Stochastic Programming Problems”, Mathematical Programming, Vol: 159, Pages: 557-569, ISSN: 0025-5610

5. Rujeerapaiboon, N, Kuhn, D, Wiesemann, W, 2015, Robust Growth-Optimal Portfolios, Management Science, Vol: 62, Pages: 2090-2109, ISSN: 1526-5501

6. Wiesemann W, Kuhn D, Sim M, 2014, Distributionally Robust Convex Optimization, Operations Research, Vol: 62(6), Pages: 1358-1376

Invited Lectures and Seminars1. Tesco Analytics, Welwyn Garden City (UK), November 2015.2. Faculty of Economics and Business, KU Leuven (Belgium),

October 2015.3. International Workshop on Vehicle Routing under Uncertainty,

TU Dortmund (Germany), September 2015.4. Workshop on Generalized Convexity and Set Computation,

London (UK), August 2015.5. 21st International MENDEL Conference, Brno (Czech

Republic), June 2015.6. School of Mathematics, University of Edinburgh (UK), March 2015.7. School of Mathematics, Computer Science & Engineering,

City University London (UK), February 2015.8. London Optimization Workshop, King’s College London (UK),

June 2014.9. Operations Group, Judge Business School, University of

Cambridge (UK), April 2014

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Imperial College London

Department of Chemical EngineeringProfessor Nilay Shah, FREng, Professor of Process Systems Engineering, Director CPSEProfessor Claire S. Adjiman, FREng, Professor of Chemical EngineeringDr Benoît Chachuat, Reader in Process Systems EngineeringDr Peter DiMaggio, Senior LecturerProfessor Amparo Galindo, Professor of Physical ChemistryDr Gonzalo Guillén-Gosálbez, Reader in Process Systems EngineeringDr Adam Hawkes, Senior Lecturer in Energy SystemsProfessor George Jackson, Professor of Chemical PhysicsDr Cleo Kontoravdi, Senior LecturerDr J Krishnan, Senior LecturerProfessor Geoffrey C. Maitland, FREng, Professor of Energy EngineeringProfessor Athanasios (Sakis) Mantalaris, Professor of BioSystems EngineeringProfessor Erich Müller, Professor of ThermodynamicsProfessor Costas C. Pantelides, FREng, Professor of Chemical EngineeringProfessor Nina F. Thornhill, FREng, Professor of Process Automation

Business SchoolDr Wolfram Wiesemann, Assistant Professor

Centre for Environmental PolicyDr Niall MacDowell, Lecturer in Energy and Environmental Technology and Policy

Department of Civil and Environmental EngineeringDr James Keirstead, Lecturer

Department of ComputingDr Marc Deisenroth, Lecturer in Statistical Machine LearningDr Ruth Misener, Lecturer in ComputingDr Panos Parpas, Senior Lecturer

Department of Earth Science & EngineeringProfessor Nigel Brandon, OBE FREng, Director of the Sustainable Gas Institute (SGI)

Emeritus and Honorary AcademicsProfessor Roger BensonDr Graham ElkesProfessor John PerkinsProfessor Efstratios (Stratos) PistikopoulosProfessor Berc Rustem, Professor of ComputingProfessor Paul RutterProfessor Roger W. H. Sargent

University College London

Department of Chemical EngineeringDepartment of Chemical EngineeringProfessor I. David Bogle, FREng, Professor of Chemical Engineering and Head of UCL Graduate SchoolDr Vivek Dua, Senior LecturerProfessor Eric S. Fraga, Professor of Process Systems EngineeringDr Federico Galvanin, LecturerProfessor Lazaros Papageorgiou, Professor of Chemical EngineeringProfessor Eva Sørensen, Deputy Head for Education and Professor Chemical EngineeringDr Michail Stamatakis, Lecturer

Department of Biochemical EngineeringDr Alexandros Kiparissides, Lecturer

CPSE Academics and Staff Directory

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Academic Staff

Professor Nilay Shah (CPSE Director) n.shah@imperial.ac.ukProfessor Claire S Adjiman c.adjiman@imperial.ac.ukProfessor I David L Bogle d.bogle@ucl.ac.ukProfessor Nigel Brandon n.brandon@imperial.ac.ukDr Benoît Chachuat b.chachuat@imperial.ac.ukDr Marc Deisenroth m.deisenroth@imperial.ac.ukDr Peter DiMaggio p.dimaggio@imperial.ac.ukDr Vivek Dua v.dua@ucl.ac.ukProfessor Eric S Fraga e.fraga@ucl.ac.ukProfessor Amparo Galindo a.galindo@imperial.ac.ukDr Federico Galvanin f.galvanin@ucl.ac.ukDr Gonzalo Guillén-Gosálbez g.guillen05@imperial.ac.ukDr Adam Hawkes a.hawkes@imperial.ac.ukProfessor George Jackson g.jackson@imperial.ac.ukDr James Keirstead j.keirstead@imperial.ac.ukDr Alexandros Kiparissides alex.kiparissides@ucl.ac.ukDr Cleo Kontoravdi cleo.kontoravdi98@imperial.ac.ukDr J Krishnan j.krishnan@imperial.ac.ukDr Niall Mac Dowell n.mac-dowell06@imperial.ac.ukProfessor Geoffrey C Maitland g.maitland@imperial.ac.ukProfessor Athanasios Mantalaris a.mantalaris@imperial.ac.ukDr Ruth Misener r.misener@imperial.ac.ukProfessor Erich Müller e.muller@imperial.ac.ukProfessor Costas C Pantelides c.pantelides@imperial.ac.ukProfessor Lazaros Papageorgiou l.papageorgiou@ucl.ac.ukDr Panos Parpas p.parpasATimperial.ac.ukProf Berc Rustem b.rustem@imperial.ac.ukProfessor Eva Sørensen e.sorensen@ucl.ac.ukDr Michail Stamatakis m.stamatakis@ucl.ac.ukProfessor Nina F Thornhill n.thornhill@imperial.ac.ukDr Wolfram Wiesemann ww@imperial.ac.uk

Emeritus and Honorary Academics

Dr Graham Elkes graham.elkes@imperial.ac.ukProfessor John Perkins john.perkins@imperial.ac.ukProfessor Efstratios N Pistikopoulos e.pistikopoulos@imperial.ac.uk Professor Paul Rutter p.rutter@imperial.ac.ukProfessor Roger W.H. Sargent r.w.h.sargent@imperial.ac.uk

Research Associates

Dr Salvador Acha Izquierdo salvador.acha06@imperial.ac.ukDr Aiman Alam Nazki aiman.alam-nazki07@imperial.ac.ukDr Adrian Aguirre a.aguirre@ucl.ac.ukDr John Blamey j.blamey07@imperial.ac.ukDr Carlos Henrique Correia Braga c.correia-braga@imperial.ac.ukDr Sara Fadda s.fadda@imperial.ac.ukDr Sara Giarola s.giarola10@imperial.ac.ukDr Miao Guo miao.guo06@imperial.ac.ukDr Andrew Haslam a.haslam@imperial.ac.ukDr Carmelo Herdes Moreno c.herdes@imperial.ac.ukDr Philip Jedrzejewski philip.jedrzejewski07@imperial.ac.ukDr Maria Guadalupe Serratos Jimenez m.jimenez-serratos@imperial.ac.uk

Dr Do Yeon Kim d.kim@imperial.ac.ukDr Oleksiy Klymenko o.klymenko@imperial.ac.ukDr Sergei Kucherenko s.kucherenko@imperial.ac.ukDr Kamal Kuriyan kkuriyan@ic.ac.ukDr Romain Lambert romain.lambert 08@imperial.ac.ukDr Lianfang Cai l.cai@imperial.ac.ukDr Songsong Liu s.liu@ucl.ac.ukDr Ryan Luong vu.luong05@imperial.ac.ukDr Evgenia Mechleri e.mehleri@imperial.ac.ukDr Marta Moreno Benito marta.moreno.benito@ucl.ac.ukDr Jordan Muscatello jordan.muscatello05@imperial.ac.ukDr HongXing Niu h.niu@imperial.ac.ukDr Antonio Marco Pantaleo a.pantaleo@imperial.ac.ukDr Remigijus Paulavicius remigijus.paulavicius@imperial.ac.ukDr Bharat Kumar Varma Penumathsa b.penumathsa@imperial.ac.ukDr Pedro Rivotti p.rivotti@imperial.ac.ukDr Nouri Samsatli n.samsatli@imperial.ac.ukDr Sheila Samsatli s.samsatli@imperial.ac.ukDr Saurabh Mahesh Kumar Shah saurabh.shah10@imperial.ac.ukDr Mahdi Sharifzadeh mahdi.sharifzadeh08@imperial.ac.ukDr Javier Silvente j.silvente@ucl.ac.ukDr Edward Smith edward.smith05@imperial.ac.ukDr Si Nga Sou si.sou07@imperial.ac.ukDr Isaac Sugden i.sugden@imperial.ac.ukDr Panagiotis Theodorakis p.theodorakis@imperial.ac.ukDr Koen Van Dam k.van-dam@imperial.ac.ukDr Xiaonan Wang xiaonan.wang@imperial.ac.ukDr Yang Yang yang.yang@imperial.ac.ukDr Ioannis Zacharoudiou i.zacharoudiou@imperial.ac.ukDr Di Zhang di.zhang.09@ucl.ac.ukDr Sophie Zemenides s.zemenides@imperial.ac.ukDr Fessehaye Zemichael f.zemichael@imperial.ac.uk

Support Staff

CPSE Administration and Research OfficerMiss Cristina Romano c.romano@imperial.ac.uk

CPSE External Relations ManagerMiss Senait Selassie s.selassie@imperial.ac.uk

Head of Computing Services Mr Graham Stuart g.stuart@imperial.ac.uk

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“Continuing advances in computing power and artificial intelligence will extend the reach, capability and usability of process systems engineering to help industry and society deal with the challenges that confront us all in the next century.”

CPSE Research Project ListProfessor Paul Rutter

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Ali Salim Al QahtaniTechnical, Economic and Environmental Impact of Future FuelFormulationsSupervisor: Prof Nilay ShahStart date: October 2010Finish date: October 2016

Adam AlexandrosIntegrated Heating and Power Systems for DwellingsSupervisor: Prof Eric FragaStart date: October 2011Finish date: May 2016

Folashade AkinmolayanReal‐Time Operational Risk Management through Advanced Multi‐Scale ModellingSupervisors: Prof Eva Sørensen and Prof Nina ThornhillStart date: August 2011Finish date: July 2016

Yasmeen AldawsariSystems Analysis of Transport Decarbonisation OptionsSupervisor: Prof Nilay ShahStart date: September 2013Finish date: September 2017

Amos B. AlejiExperimental and Modelling of Viscosity and Density of Mixtures of Crude oil + CO2

Supervisors: Prof Geoffrey Maitland and Prof Martin TruslerStart date: February 2011Finish date: August 2016

Sakhr AlhuthaliUnderstanding the Interplay Between Upstream and Downstream Bioprocessing by a Sequence of Mathematical ModelsSupervisor: Dr Cleo KontoravdiStart date: October 2015Finish date: May 2019

Mark C. AllenbyDevelopment of a Bio‐Inspired in Silico‐in Vitro Platform: Towards Personalised Healthcare through Optimisation of a Bone Marrow Mimicry BioreactorSupervisors: Prof Athanasios Mantalaris and Prof Efstratios PistikopoulosStart date: October 2013Finish date: April 2017

Nihal AlmuraikhiStem Cell BioprocessingSupervisor: Prof Athanasios MantalarisStart date: October 2010Finish date: August 2016

Diego Alonso MartinezProfiling the Methylome Targets of Histone Lysine MethyltransferasesSupervisor: Dr Peter DiMaggioStart date: September 2013Finish date: September 2017

Tamador AlsobaieStem Cell BioprocessingSupervisor: Prof Athanasios MantalarisStart date: May 2012Finish date: January 2016

Daniel E. AlumaModel‐Based Optimisation of the Operation of Integrated Natural Gas Production & Processing NetworksSupervisors: Prof Nilay Shah and Prof Costas PantelidesStart date: November 2012Finish date: November 2016

Oluwamayowa AmusatDesign of Renewables‐Based Integrated Energy Systems for Stand‐Alone Continuous ProcessesSupervisor: Prof Eric FragaStart date: November 2013Finish date: November 2016

CPSE Research Project List

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Benaiah Uchechukwu AnabaraonyeExperimental and Modelling Studies of Reservoir Minerals Dissolution Following CO2 InjectionSupervisor: Prof Geoffrey MaitlandStart date: October 2013Finish date: October 2016

William AshworthSystems Biology of the LiverSupervisors: Prof David Bogle and Dr Nathan Davies (UCL Division of Medicine)Start date: October 2013Finish date: May 2017

Vitali AvagyanEssays on Risks and Profitability of the UK Electricity IndustrySupervisors: Prof Berc Rustem, Dr Panos Parpas and Prof Richard GreenStart date: October 2012Finish date: September 2016

Vijay AvinashIntegration of Decentralised Energy Resources with the Electricity Balancing SystemSupervisor: Dr Adam HawkesStart date: April 2014Finish date: April 2017

Styliani AvraamidouDistributed Multi‐Parametric Model Protective Control Applied on Biological and Biomedical ProcessesSupervisors: Prof Athanasios Mantalaris and Prof Efstratios PistikopoulosStart date: October 2014Finish date: April 2018

Radu Baltean-LugojanStructure Exploitation in Large Scale Non‐Convex OptimizationSupervisor: Dr Ruth MisenerStart date: April 2015Finish date: April 2018

Davide BasconeModelling and Optimisation of the Nuclear Fuel CycleSupervisor: Prof Eric FragaStart date: March 2015Finish date: March 2019

Asif BhattiSynthesis and Design of Biological Systems Under UncertaintySupervisor: Dr Vivek DuaStart date: October 2010Finish date: September 2016

Hao BianStudies of Production, Inhibition and Exchange Processes forGas HydratesSupervisor: Prof Geoffrey MaitlandStart date: July 2013Finish date: June 2016

Moiz BohraOptimising Qatar’s Transition to Renewable Energy through Model-Based AnalysisSupervisor: Professor Nilay ShahStart date: April 2016End date: December 2019

Aaron BorgCharacterising the Function of Chromatin‐Modifying Protein ComplexesSupervisor: Dr Peter DiMaggioStart date: August 2012Finish date: July 2016

Jonathan BoschRenewable Energy Potentials for Global Energy Systems ModelsSupervisor: Dr Adam HawkesStart date: October 2014Finish date: June 2017

Susana Isabel Brito dos SantosIn Vitro Erythropoiesis in a 3D Bone Marrow Biomimicry: Reproducing Physiologic Biochemical and Microenvironmental Factors Involved in Red Blood Cell FormationSupervisors: Prof Athanasios Mantalaris and Dr Nicki PanoskaltsisStart date: March 2014Finish date: March 2018

Pantelis BroukosUrban Energy SystemsSupervisors: Prof Nilay Shah and Dr James KeirsteadStart date: September 2012Finish date: December 2015

Sara BudinisENERGY‐SMARTOPSSupervisor: Prof Nina ThornhillStart date: September 2011Finish date: December 2015

Gizem BuldumBacterial Cellulose ProductionSupervisor: Prof Athanasios MantalarisStart date: October 2011Finish date: October 2016

Gonzalo Bustos-TuruIntegrated Modelling of Future Urban Energy SystemsSupervisor: Prof Nilay ShahStart date: March 2014Finish date: March 2017

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Renato CabralA Quantification of the Value Provided by Flexible Oxy‐Combustion CCS to the UK Energy SystemSupervisor: Dr Niall Mac DowellStart date: October 2015Finish date: September 2018

Claudio CalabreseViscosity and Density of Reservoir Fluids under CO2 AdditionSupervisors: Prof Geoffrey Maitland and Prof Martin TruslerStart date: November 2013Finish date: October 2016

Andres Calderon VargeraOptimisation of Biomass‐Based Supply ChainsSupervisor: Prof Lazaros PapageorgiouStart date: May 2013Finish date: April 2017

Raúl Calvo SerranoProcess Optimisation and Sustainability AnalysisSupervisor: Dr Gonzalo Guillén GosálbezStart date: April 2016Finish date: March 2019

Juan Sebastian Campos SalazarMultilevel Optimization for Large Scale Semidefinite ProgrammingSupervisor: Dr Panos ParpasStart date: October 2013Finish date: October 2017

Vassilis M. CharitopoulosUncertainty-Aware Planning and Scheduling in the Process IndustriesSupervisors: Dr Vivek Dua and Prof Lazaros PapageorgiouStart date: September 2015Finish date: September 2019

Florence Yu Tsing ChowThe Effect of Impurities on the Interfacial Tension betweenCO2 and Reservoir FluidsSupervisor: Prof Geoffrey MaitlandStart date: September 2012Finish date: September 2015

Cheng-Ta ChuGlobal Electricity Sector Decarbonisation ModellingSupervisor: Dr Adam HawkesStart date: October 2015Finish date: October 2019

Edward James CloseThe Derivation of Bioprocess Understanding from Mechanistic Models of ChromatographySupervisors: Prof Eva Sørensen and Dr Dan Bracewell (UCL)Start date: September 2010Finish date: October 2014

Constanza Cumicheo MelgarejoThe Combination of Bioenergy, Natural Gas and CCS for Negative EmissionsSupervisors: Dr Niall Mac Dowell and Prof Nilay ShahStart date: November 2015Finish date: June 2019

Ibrahim DaherThe Effect of Salt Precipitation on Permeability and Porosity in Fractured Carbonates SystemSupervisors: Dr John Crawshaw and Prof Geoffrey MaitlandStart date: January 2013Finish date: January 2017

Matthew Thomas DarbyFirst‐Principles Simulations of Molecular Phenomena on Bimetallic Hydrogenation CatalystsSupervisor: Dr Michail StamatakisStart date: October 2013Finish date: May 2016

Pedro de Oliveira FilhoDevelopment, Implementation and Application of a Language for Modelling Uncertainty in Design and Process OptimisationSupervisor: Prof Eric FragaStart date: October 2015Finish date: September 2019

Aikaterini DiamantiDesign of Optimal Reaction Conditions: Temperature and Solvent EffectsSupervisors: Prof Claire Adjiman and Prof Amparo GalindoStart date: October 2012Finish date: October 2016

David Dorantes RomeroCapture and Analysis of Process Connectivity and TopologySupervisor: Prof Nina ThornhillStart date: October 2012Finish date: September 2018

Daniel Kunisch EriksenMolecular Modelling and Thermodynamics of Oil Systems in the Presence of Brine and CO2

Supervisors: Prof Amparo Galindo and Prof George JacksonStart date: October 2012Finish date: August 2016

Karl FairhurstMolecular Simulation of Associating Fluids, Using a Combination of Molecular Dynamics (MD) and Monte Carlo (MC) Simulations, with Coarse‐Grained ModelsSupervisors: Prof Erich Müller and Prof George JacksonStart date: October 2015Finish date: September 2019

90

Sara FebraMolecular Systems Engineering Methods for Solubility Predictionof Active Pharmaceutical IngredientsSupervisor: Prof Amparo GalindoStart date: March 2014Finish date: March 2017

Christina-Anna GatsiouCrystal Structure PredictionSupervisors: Prof Claire Adjiman and Prof Costas PantelidesStart date: March 2012Finish date: March 2016

Anastasia GeorgiouGeneration of Mineralised Cellular Constructs Using Mouse Embryonic Stem Cells Encapsulated in Alginate Hydrogels and Cultured within a Custom‐Made Rotating Wall Vessel Perfusion BioreactorSupervisor: Prof Athanasios MantalarisStart date: October 2009Finish date: January 2016

Solomos GeorgiouDecarbonisation of Food Supply Chains: A Holistic ApproachSupervisors: Prof Nilay Shah and Dr Christos MarkidesStart date: October 2015Finish date: September 2019

Cher Hui GoeyCascading Effects in Bioprocessing: The impact of Cell Culture Environment on Mammalian Cell Behaviour and Host Cell Protein SpeciesSupervisor: Dr Cleo KontoravdiStart date: February 2013Finish date: February 2017

Smitha GopinathDeveloping a Methodology for Integrated Molecular and Process DesignSupervisors: Prof George Jackson, Prof Claire Adjiman and Prof Amparo GalindoStart date: September 2013Finish date: March 2017

Edward GrahamThe Integrated Molecular and Process Modelling of Carbon Dioxide Capture in Amine SolventsSupervisors: Prof Claire Adjiman, Prof George Jackson and Prof Amparo GalindoStart date: December 2014Finish date: December 2017

Boram GuModelling of RO Membrane Process Performance and Transport Phenomena for Performance Analysis and OptimisationSupervisors: Prof Claire Adjiman and Prof Yun XuStart date: April 2014Finish date: October 2016

Yingjian GuoModelling the Role of Gas T&D Infrastructure in Future Low Carbon Energy SystemsSupervisor: Dr Adam HawkesStart date: October 2015Finish date: April 2019

Clara HeubergerEnergy System Optimisation and Technology Valuation, in Particular of Flexible CCSSupervisors: Dr Niall Mac Dowell, Prof Nilay Shah and Dr Iain StaffellStart date: January 2015Finish date: June 2018

Ching-Pang HoOptimization Algorithms for Multiscale ModelsSupervisors: Dr Panos Parpas and Dr Wolfram WiesemannStart date: October 2012Finish date: September 2016

Rayane HoballahSolubility of Gases in Water or Brines at Reservoir ConditionsSupervisors: Prof Martin Trusler and Prof Geoffrey MaitlandStart date: December 2012Finish date: February 2017

Vahan HovhannisyanMulti‐Level Convex Optimisation in Machine LearningSupervisors: Dr Panos Parpas and Dr Stefanos ZafeiriouStart date: September 2013Finish date: September 2017

Sei HoweSingularly Perturbed Optimal Control SystemsSupervisor: Dr Panos ParpasStart date: October 2012Finish date: March 2017

Panatpong HutacharoenPrediction of Octanol‐Water Partition Coefficients of Active Pharmaceutical Ingredients by the SAFT‐γ Mie Group‐Contribution Equation of StateSupervisors: Prof Claire Adjiman, Prof Amparo Galindo and Prof George JacksonStart date: May 2013Finish date: October 2016

Frederike JaegerFlow of Fluids through Porous Media with Application to Membranes: from the Molecular to the Continuum ScaleSupervisors: Prof Erich Müller and Prof Omar MatarStart date: October 2014Finish date: September 2017

91

Francisca Jalil VegaNovel Approaches to Modelling Whole System Heat DecarbonisationSupervisor: Dr Adam HawkesStart date: December 2013Finish date: April 2017

Elnaz JamiliModel‐Based Optimal Control of Non‐Viral Gene DeliverySupervisors: Dr Vivek Dua and Dr Michail StamatakisStart date: November 2012Finish date: October 2016

Erin JohnsonUK Green Gas: Exploring Sustainable Gas Potential as a Relevant Low Carbon Energy StreamSupervisor: Professor Nilay ShahStart date: October 2015Finish date: October 2018

Suela JonuzajOptimisation Approaches to Mixture DesignSupervisor: Prof Claire AdjimanStart date: August 2013Finish date: July 2017

Ashkan KaveiDevelopment and Application of Stack Segmented Fuel Cell SystemsSupervisors: Prof Nigel Brandon, Dr Gregory J Offer, Dr Billy Wu and Dr Vladimir YufitStart date: September 2015Finish date: September 2019

Nikolaos KazazakisDevelopment of Deterministic Global Optimization MethodsSupervisor: Prof Claire AdjimanStart date: September 2012Finish date: August 2016

Esma KocaProduct Release Strategies in Single and Multiple MarketsSupervisors: Dr Wolfram Wiesemann and Prof Tommaso VallettiStart date: October 2013Finish date: September 2017

Mariya KolevaOptimisation of Wastewater SystemsSupervisor: Prof Lazaros PapageorgiouStart date: March 2013Finish date: December 2016

Clea KolsterMulti‐Scale Modelling and Analysis of the Dynamic CO2 Injection and StorageSupervisors: Dr Niall Mac Dowell and Dr Sam KrevorStart date: October 2014Finish date: October 2017

Qingyuan KongAn Optimisation‐Based Framework for the Conceptual Design of Reaction‐Separation ProcessesSupervisor: Prof Nilay ShahStart date: October 2014Finish date: June 2018

Georgia KouyialisExploiting Symmetry in Mixed Integer Non‐Linear OptimisationSupervisor: Dr Ruth MisenerStart date: October 2014Finish date: September 2017

Gabriel LauDroplets: From Molecular Nanoclusters to the Atmospheric AerosolsSupervisor: Prof George JacksonStart date: March 2013Finish date: September 2016

Georgia LazarouModelling the Effect of pH on the Thermodynamics of Electrolyte Solutions Using the Statistical Associating Fluid TheorySupervisors: Prof Claire Adjiman, Prof Amparo Galindo, Prof George Jackson and Prof Erich MüllerStart date: October 2013Finish date: September 2017

Duncan LeesonEnergy Cascading in Complex Downstream OperationsSupervisors: Prof Nilay Shah, Dr Paul Fennell and Dr Niall Mac DowellStart date: October 2014Finish date: April 2018

David LengFault Propagation, Detection and Analysis in Process SystemsSupervisor: Prof Nina ThornhillStart date: September 2013Finish date: June 2018

Yunjie LiaoDevelopment and Validation of a Model of Energy Differential Production Across the Liver SinusoidSupervisors: Prof David Bogle and Dr Nathan Davies (UCL Division of Medicine)Start date: October 2015Finish date: September 2019

Phantisa LimleamthongSystematic Computer Aided Process Engineering Tools for the Optimal Design and Planning of Sustainable Chemical ProcessesSupervisor: Dr Gonzalo Guillén‐GosálbezStart date: April 2016Finish date: March 2019

92

Tom LindeboomMolecular Origins of the Thermodynamic Properties, Phase Separation Behaviour and Structure of Biomolecules in Aqueous SolutionsSupervisors: Prof George Jackson and Prof Amparo GalindoStart date: October 2015Finish date: September 2019

Maximilian LularevicA Combined Multi‐Scale Modelling and Experimental Investigation of the Effects of Lactate Metabolism on Mammalian Cell BioprocessingSupervisors: Dr Alexandros Kiparissides and Dr Cleo KontoravdiStart date: September 2015Finish date: September 2019

Robert MacFarlaneThe Production of 3‐Dimensional Mineralised Cellular Implants for Bone Tissue Engineering ApplicationsSupervisor: Prof Athanasios MantalarisStart date: October 2013Finish date: September 2017

Nikiforos MaragkosNovel Composite Materials Design for Economic Infrastructure EquipmentSupervisors: Prof Efstratios Pistikopoulos and Prof Alexander BismarckStart date: October 2009Finish date: PENDING (Interruption of Studies)

Amit M. ManthanwarMultiscale Design, Robust Optimisation and Robust Model Predictive Control of Fuel Cell Energy SystemsSupervisor: Prof Efstratios PistikopoulosStart date: February 2012Finish date: May 2016

Kristian Mc CaulA Multiscale and Multiphysics Modelling Framework for Processes Involved in Production of Fuels from LignocellulosesSupervisors: Prof Nilay Shah, Dr Cleo Kontoravdi and Prof Yun XuStart date: September 2013Finish date: March 2017

Calum J McIntoshControlling the Quality of Novel Glycoprotein TherapeuticsSupervisor: Dr Cleo KontoravdiStart date: November 2015Finish date: November 2019

Govind MenonElucidating Temporal and Spatial Aspects of Cellular Information ProcessingSupervisor: Dr J KrishnanStart date: October 2014Finish date: April 2018

Miten MistryIntegrating Mixed Integer Nonlinear Programming and Satisfiability Modulo Theories for Next‐Generation Optimisation AlgorithmsSupervisor: Dr Ruth MisenerStart date: October 2015Finish date: September 2019

Nur Amirah Izzati Mohd NoorIndustrial Smart GridSupervisor: Prof Nina ThornhillStart date: September 2013Finish date: September 2017

Eðvald MollerModel Development and EvaluationSupervisors: Prof Nilay Shah and Prof Lazaros PapageorgiouStart date: November 2010Finish date: January 2018

Ioana NascuAdvances in Explicit/Multi‐Parametric Model Predictive Control with applications in AnaesthesiaSupervisor: Prof Efstratios PistikopoulosStart date: January 2012Finish date: April 2016

Dimitrios NerantzisDeterministic Global Optimisation TechniquesSupervisor: Prof Claire AdjimanStart date: September 2012Finish date: September 2016

Andreas NikolaouMulti‐Scale Modelling of Light‐limited Growth in Microalgae Production SystemsSupervisor: Dr Benoît ChachuatStart date: November 2011Finish date: November 2015

Richard OberdieckTheoretical and Algorithmic Developments in Multi‐Parametric Optimization and ControlSupervisors: Prof Athanasios Mantalaris and Prof Efstratios PistikopoulosStart date: September 2013Finish date: August 2016

Funmilayo OlabodeParameter Estimation Using Neural NetworksSupervisor: Dr Vivek DuaStart date: January 2014Finish date: January 2019

93

Anna PanteliBiorenewable Value Chain Optimization with Multi‐Layered Value Chains and Advanced AnalyticsSupervisor: Prof Nilay ShahStart date: July 2014Finish date: July 2017

Maria PapathanasiouMulti‐Parametric Model Based Control for Nonlinear, Periodic Systems: An Application to Biopharmaceutical ProcessesSupervisors: Prof Efstratios Pistikopoulos and Prof Athanasios MantalarisStart date: November 2012Finish date: November 2016

Nehal PatelComparison of Chromatographic and Two‐Phase Separations for Novel BiopharmaceuticalsSupervisor: Prof Eva SørensenStart date: September 2012Finish date: September 2016

Carlos Perez-GalvanGlobal Optimisation of Dynamic Process SystemsSupervisor: Prof David BogleStart date: January 2013Finish date: December 2016

Nikola PericTowards the Next Generation of Algorithms and Software for Global Optimization of Energy and Environmental SystemsSupervisor: Dr Benoît ChachuatStart date: October 2013Finish date: September 2016

Stefan PfenningerMulti‐Scale Energy Systems ModellingSupervisor: Dr James KeirsteadStart date: October 2012Finish date: September 2015

Catalina PinoElectrodes by Design ‐ Improved Electrodes for Redox Flow BatteriesSupervisor: Prof Nigel BrandonStart date: October 2015Finish date: September 2019

Channarong PuchongkawarinOptimisation‐Based Methodology for the Design and Operation of Sustainable Wastewater Treatment FacilitiesSupervisors: Dr Benoît Chachuat and Prof David StuckeyStart date: November 2011Finish date: February 2016

Ana Luz Quiroga CampanoMathematical Modelling and Experimental Validation for the Optimization and Control of Mammalian Cell Culture SystemsSupervisor: Prof Athanasios MantalarisStart date: October 2012Finish date: October 2016

Sadia RahmanComputer Simulation of Coarse‐Grained Models of Ionic SurfactantsSupervisors: Prof Erich Müller, Prof Amparo Galindo and Prof George JacksonStart date: September 2012Finish date: August 2016

Jai RajyaguruRigorous Numerical Analysis with Polynomial Models: Applications to Implicit and Differential‐Algebraic EquationsSupervisor: Dr Benoît ChachuatStart date: October 2011Finish date: February 2016

Shakeel RamjaneeIntegrated Production Modelling Systems for the Upstream Oil & Gas Industry and Field PerformanceSupervisors: Prof Nilay Shah, Dr Benoît Chahuat and Prof Ann MuggeridgeStart date: October 2015Finish date: October 2018

Krisztian RonaszegiWater Splitting for Hydrogen Production for Use in DwellingsSupervisor: Prof Eric FragaStart date: May 2011Finish date: September 2016

Daniel RossMulti‐Scale Simulation of the Transport of Hydrocarbons in Porous Engine DepositsSupervisor: Prof Erich MüllerStart date: October 2012Finish date: September 2016

Victor Sanchez TarreA Combined Multi‐Scale Modelling and Experimental Approach to Optimize Algal Culture Efficiency at the Metabolic, Process and Reactor Design LevelSupervisors: Dr Alexandros Kiparissides and Dr Gary LyeStart date: September 2015Finish date: September 2019

Symeon SavvopoulosMathematical Modelling of Chronic Lymphocytic LeukaemiaSupervisor: Prof Athanasios MantalarisStart date: March 2014Finish date: March 2018

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Oliver SchmidtInnovation Potential of Energy Storage Technologies and the Value of Storage in Low‐Carbon Energy SystemsSupervisor: Dr Adam HawkesStart date: October 2015Finish date: October 2018

Marzia SesiniGas Storage and its Strategic Coordination within the EU Market: A Qualitative and Quantitative ApproachSupervisor: Dr Adam HawkesStart date: October 2015Finish date: October 2019

Olivia SloanCombined CO2 Storage and Enhanced Oil Recovery in the North Sea. Rock Heterogeneity and Flow in Geologic Systems with Low Flow Potential – applications to Subsurface CO2 InjectionSupervisors: Dr Sam Krevor, Dr Niall McDowell and Dr Jerome Neufeld (University of Cambridge)Start date: October 2015Finish date: October 2019

Bowen SongSolid Oxide Fuel CellSupervisor: Prof Nigel BrandonStart date: October 2015Finish date: October 2018

Si Nga SouUnderstanding the Impact of Bioprocess Conditions on Monoclonal Antibody Glycosylation in Mammalian Cell Cultures through Experimental and Computational AnalysesSupervisors: Dr Cleo Kontoravdi and Dr Karen M PolizziStart date: October 2011Finish date: February 2016

Graham StevensonEngineering Ceramic Scaffold Electrodes for Solid Oxide Fuel Cells and Solid Oxide Electrolyzer CellsSupervisor: Prof Nigel BrandonStart date: September 2015Finish date: September 2019

Flávio StrutzelEconomically Optimal Integrated Process and MPC Control DesignSupervisor: Prof David BogleStart date: October 2014Finish date: September 2018

Carlos Ricardo Suarez HerediaDevelopment of a Combined Mathematical and Experimental Platform for the Design and Optimisation of Metabolically Balanced Nutrient Supplementation Strategies in Semi‐Continuous Mammalian Cell CulturesSupervisor: Dr Alexandros KyparissidisStart date: April 2016Finish date: March 2020

Muxin SunDesign of Tractable MPC and NCO‐Tracking Controllers using Parametric ProgrammingSupervisors: Prof Efstratios Pistikopoulos and Dr Benoît ChachuatStart date: September 2013Finish date: September 2016

Thapanar SuwanmajoModelling and Systems Engineering Approaches for Elucidating Dynamics and Information Processing of Multi-Site Phosphorylation SystemsSupervisor: Dr Jawahar KrishnanStart date: April 2011Finish date: July 2016

Asma TahlawiDevelopment of a Three‐Dimensional Biomimicry for the Culture of Normal and Abnormal Haematopoietic CellsSupervisor: Prof Athanasios MantalarisStart date: September 2013Finish date: November 2017

Naveed TariqModel Based Analysis of Low Carbon Energy Pathways based on Natural GasSupervisor: Prof Nilay Shah and Prof Paul FennellStart date: October 2012Finish date: October 2016

Quang TranSampling Algorithms for Stochastic Programming Using ImportanceSampling and Markov Chain Monte CarloSupervisors: Prof Berc Rustem and Dr Panos ParpasStart date: October 2011Finish date: June 2016

Cristian TrianaHeat Integration for Bioethanol Process from Lingocellulosic BiomassSupervisors: Prof Eric Fraga and Prof Eva SørensenStart date: October 2011Finish date: June 2016

Argyro TsipaConnecting Transcriptional Regulation to Microbial Growth Kinetics in Cultures of Pseudomonas PutidaSupervisors: Prof Athanasios Mantalaris and Prof Efstratios PistikopoulosStart date: September 2011Finish date: February 2016

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Chonlatep UsakuAn Integrated Experimental and Modelling Approach for the Study of Apoptosis in GS‐NS0 Cell CulturesSupervisors: Prof Athanasios Mantalaris and Prof Efstratios PistikopoulosStart date: October 2010Finish date: March 2016

Mario VillanuevaSet‐Theoretic Methods for Analysis, Estimation and Control of Nonlinear SystemsSupervisor: Dr Benoît ChachuatStart date: October 2011Finish date: September 2015

Yukun WangSet Theoretic Approaches in Estimation and Optimization of Large‐Scale Process SystemsSupervisor: Dr Benoît ChachuatStart date: October 2015Finish date: March 2019

Carmen WoutersOptimal Design and Regulation of Residential Distributed Energy SystemsSupervisors: Prof Eric Fraga and Dr Adrian JamesStart date: February 2013Finish data: February 2017

Dionysios XenosENERGY‐SMARTOPSSupervisor: Prof Nina ThornhillStart date: September 2011Finish date: December 2015

Iván Ying XuanElectricity Demand‐Side Response from Heavy Industrial LoadsSupervisor: Prof Nina ThornhillStart date: October 2015Finish date: October 2018

Joseph YaoBiomass Combustion with In‐Situ CO2 Capture Via the Calcium LoopSupervisor: Prof Geoffrey MaitlandStart date: October 2012Finish date: September 2015

Mauricio Javier Zamorano MosnaimHuman Dental Pulp Stem Cells: Characterisation and In Vitro 3D Bone OntogenesisSupervisor: Prof Athanasios MantalarisStart date: January 2012Finish date: February 2016

96

Dr Ozlem AkgulOptimisation of Bioenergy Supply ChainsSupervisors: Professor Lazaros Papageorgiou and Professor Nilay ShahEmployer: Baringa

Dr Aiman Alam NazkiElucidating the Spatial Organization and Control of Information Processing in Cell Signalling Networks: From Network and Enzymatic Building Blocks to Concrete SystemsSupervisor: Dr Jawahar KrishnanEmployer: Awarded EPSRC Prize Fellowship, Imperial College London

Dr Saif Al GhafriPhase Behaviour and Physical Properties of Reservoir Fluids Under Addition of Carbon DioxideSupervisors: Professor Martin Trusler and Professor Geoffrey MaitlandEmployer: Research Fellow, University of Western Australia

Dr Ahmed AlhajajMultiscale Design and Analysis of CO2 Capture, Transport and Storage NetworksSupervisors: Professor Nilay Shah, Professor Nigel Brandon and Professor Velisa VesovicEmployer: Masdar Institute

Dr Christos ArgyropoulosA Combined Immersed Boundary/Phase‐Field Method for Simulating Two‐Phase Pipe flowsSupervisor: Dr Edo BoekEmployer: Postdoctoral Research Associate at Texas A&M University and Mary Kay O’ Connor Process Safety Center at Qatar

Dr Joakim BeckEfficient Targeted Optimisation for the Design of Pressure Swing Adsorption Systems for CO2 Capture in Power PlantsSupervisor: Professor Eric FragaEmployer: Department of Statistical Science, UCL

Dr Alireza BehjousiarIn Situ FRET Biosensors for the In Vivo Measurement of Important Metabolites during Cell CultureSupervisors: Dr Cleo Kontoravdi and Dr Karen PolizziEmployer: Gap year

Dr Shane CadoganDiffusion of CO2 in Fluids Relevant to Carbon Capture, Utilisation and Storage Supervisors: Professor Geoffrey Maitland and Professor Martin TruslerEmployer: Erlangen Graduate School in Advanced Optical Technologies (SAOT) Friedrich‐Alexander‐Universität Erlangen‐Nürnberg (FAU), Germany

Dr Inês Da Mata CecilioStudy of Simulated Moving Bed Reactor (SMBR) for Para‐Xylene ProductionSupervisor: Professor Nina ThornhillEmployer: Research Scientist at Schlumberger

Dr Emily ChapmanMicro‐Model Pore‐Scale Flow Studies of Fluid Displacement in Carbonate Rock with Application to CO2 StorageSupervisor: Dr Edo BoekEmployer: Associate at Expand Research ‐ A Company of the Boston Consulting Group

Dr Donald O’DonoghueMathematical Modelling of Ion Transport in Healthy and Cystic Fibrosis Human Airway EpitheliaSupervisor: Dr Vivek DuaEmployer: Quantitative Analyst at Irish Life Investment Managers

Dr Pongsathorn DechatiwongseA Study of the Growth and Hydrogen Production of Cyanothece sp. ATCC 51142Supervisors: Professor Klaus Hellgardt and Professor Geoffrey MaitlandEmployer: Walailak University, Nakhon Si Thammarat, Thailand

PhD Graduates 2014–2015

On completion of their studies, our graduates quickly find employment in many sectors including: industry, academia, consulting, finance and software.

97

Dr Nasim ElahiMultiscale Modelling of Carbon Capture and StorageSupervisor: Professor Nilay ShahEmployer: Research Associate, Supply Chain Optimisation, Machine learning, Data Science, Imperial College

Dr Hendrik FrentrupMolecular Simulation of Diffusive Mass Transport in Porous MaterialsSupervisor: Professor Erich MüllerEmployer: R&D Engineer, Dyson

Dr Maria Fuentes GariA Mathematical Model of Cell Cycle Heterogeneity for Personalizing Leukemia ChemotherapySupervisor: Professor Athanasios MantalarisEmployer: Process System Enterprise Limited (PSE), London, United Kingdom

Dr Zara GanaseAn Experimental Study on the Effects of Solvents on the Rate and Selectivity of Organic ReactionsSupervisors: Professor Clare Adjiman, Professor Amparo Galindo and Professor Alan Armstrong (Imperial Chemistry)Employer: Intel, Ireland

Dr David Garcia MunzerCell Cycle Heterogeneity Study by an Integrated Modelling and Experimental ApproachSupervisors: Professor Athanasios Mantalaris and Professor Efstratios PistikopoulosEmployer: Postdoctoral Associate, Novartis, Switzerland

Dr Michael HadjiyiannisDecision Under Uncertainty: Problems in Control Theory, Robust Optimization and Game TheorySupervisor: Dr Daniel KuhnEmployer: A company in Cyprus

Dr Grani HanasusantoDecision Making Under Uncertainty: Robust and Data‐Driven ApproachesSupervisors: Dr Daniel Kuhn and Dr Wolfram WiesemanEmployer: Faculty member at UT Austin

Dr Abdihakim HassanModelling Solvent Mixtures and their Effects on ReactionsSupervisors: Professor Claire Adjiman and Professor Amparo GalindoEmployer: Shell

Dr Philip JedrzejewskiA Platform for the Optimisation of Metabolic Pathways for Glycosylation to Achieve a Narrow and Targeted Glycoform DistributionSupervisor: Dr Cleo KontoravdiEmployer: Gap year

Dr Alexandra KriegerModelling, Optimisation and Explicit Model Predictive Control of Anaesthesia Drug Delivery SystemsSupervisor: Professor Efstratios PistikopoulosEmployer: Research Assistant, RWTH Aachen, Germany

Dr Sarantos KyriakopoulosAmino Acid Metabolism in Chinese Hamster Ovary Cell CultureSupervisor: Dr Cleo KontoravdiEmployer: BioMarin, Ireland

Dr Romain LambertApproximation Methodologies for Explicit Model Predictive Control of Complex SystemsSupervisor: Professor Efstratios PistikopoulosEmployer: Research Associate, Imperial College London

Dr Olga LobanovaDevelopment of Coarse‐Grained Force Fields from a Molecular Based Equation of State for Thermodynamic and Structural Properties of Complex FluidsSupervisors: Professor George Jackson and Professor Erich MüllerEmployer: Syngenta

Dr Duy LuongOptimisation for Image ProcessingSupervisors: Professor Berc Rustem, Dr Panos Parpas and Professor Daniel RueckertEmployer: Imperial College London

Dr Mithila ManageAn Investigation into the Feasibility of Integrating Intermediate‐Temperature Solid Oxide Electrolysers with Power PlantsSupervisor: Professor Eva SørensenEmployer: NNL

Dr Jan MarzinekMolecular Dynamics Modelling of Skin and Hair ProteinsSupervisors: Professor Athanasios Mantalaris and Professor Efstratios PistikopoulosEmployer: Postdoctoral Research Fellow, A *STAR/National University of Singapore, Singapore

Dr Ali MehdizadehFood Industry Supply Chain Planning with Product Quality IndicatorsSupervisor: Professor Nilay ShahEmployer: Strategy and Operation, Supply Chain (Consultancy), Birds Eye Iglo Limited

Dr Silvia PadulaCapacity Planning for Water Supply NetworksSupervisor: Professor Lazaros PapageorgiouEmployer: University of Manchester

98

Dr Antonio Marco PantaleoPerspectives on the Role of Bioenergy for Distributed Heat and Power GenerationSupervisor: Professor Nilay ShahEmployer: Imperial College London

Dr Nicole PapaioannouEnvironmental Impact Assessment and Optimization of Urban Energy SystemsSupervisor: Professor Nilay ShahEmployer: Principal Consultant ‐ Gas & Power at Wood Mackenzie

Dr Olga ParkesDefining a Comprehensive Methodology for Sustainability Assessment of Mega‐Event ProjectsSupervisors: Professor David Bogle and Professor Paola LettieriEmployer: UK Dept of Energy and Climate Change

Dr Eleni PefaniModelling and Optimisation Based Drug Delivery Systems for the Treatment of Acute Myeloid Leukemia (AML)Supervisors: Professor Efstratios Pistikopoulos and Dr Nicki PanoskaltsisEmployer: GlaxoSmithKline, Stevenage, United Kingdon

Dr Cheng PengChemical Interactions Between CO2 Acidified Aqueous Fluids and Carbonate MineralsSupervisors: Professor Geoffrey Maitland, Professor Martin Trusler and Dr John CrawshawEmployer: Shell Global Solutions International B.V., Rijswijk, Netherlands

Dr Vladimir RoitchOptimisation Applied to Cloud ComputingSupervisors: Dr Daniel Kuhn and Dr Wolfram WiesemannEmployer: Lecturer at City University

Dr Pedro RivottiMulti‐Parametric Programming and Explicit Model Predictive Control of Hybrid SystemsSupervisor: Professor Efstratios PistikopoulosEmployer: Research Associate, Imperial College London

Dr Cyrus SiganporiaProduction Planning for BiopharmacicalsSupervisor: Professor Lazaros PapageorgiouEmployer: Research Associate, University College London

Dr Erini SiougkrouSystematic Methods for Solvent Design: Towards Better Reactive ProcessesSupervisors: Professor Claire Adjiman and Professor Amparo GalindoEmployer: Marie Curie Research Fellow at National Technical University of Athens

Dr Saurabh Mahesh Kumar ShahMulti-Scale Pore Imaging of Multiphase Flow in Porous MediaSupervisor: Dr Edo BoekEmployer: QCCSRC Experimental Officer, Imperial College London

Dr Roochi SolankiModelling of a Two‐Phase Thermofluidic Oscillator for Low‐Grade Heat UtilisationSupervisors: Dr Christos Markides and Professor Amparo GalindoEmployer: Carbon Credentials

Dr Ioanna StefaniUnravelling the Progression of Endoplasmic Reticulum Stress in Familial Alzheimer’s DiseaseSupervisors: Dr Cleo Kontoravdi and Dr Karen PolizziEmployer: ICON (Medical Consulting)

Dr Ailing TeoExploring New Bioprocess Considerations for Cardiomyogenesis of Embryonic Stem CellsSupervisors: Professor Athanasios Mantalaris and Professor Lim MayasariEmployer: Associate Patent Examiner at Intellectual Property Office of Singapore

Dr Lingjian YangOptimisation Approaches for Data Mining in Biological SystemsSupervisor: Professor Lazaros PapageorgiouEmployer: PDRA at University of Manchester

Dr Lara YarosonForce Field Parameters from the SAFT Equation of State for the Molecular Simulation of Fused MoleculesSupervisors: Professor George Jackson, Professor Erich Müller and Professor Amparo GalindoEmployer: Syngenta

Dr Stamatina ZavitsanouModeling and Multi Parametric Control Drug Delivery Systems for Diabetes Type 1Supervisor: Professor Efstratios PistikopoulosEmployer: Postdoctoral Research Scholar at SEAS, Harvard University

Centre for Process Systems Engineering (CPSE), Imperial College London, Roderic Hill Building, South Kensington Campus, London SW7 2AZ, Email: cpse@imperial.ac.uk, Phone: +44 (0)207 594 6605/11 http://www3.imperial.ac.uk/centreforprocesssystemsengineering