telecoms, media & technology - sessions ai …...anthony macciola- chief innovation officer,...

Welcome Address

09:00 - 09:201) Deliver - CxOs and Top-Level Business Leaders

Visit Deliver Stage for Opening Keynote

09:00 - 09:502) Implement - Senior Strategists and Heads ofFunction

Visit Deliver Stage for Opening Keynote

09:00 - 10:003) Develop - Heads of Tech and Practitioners

Creating A Data Literate, AI Ready Businessfrom The Top Down

09:00 - 10:30Lounge 1: AI Forbes Boardoom - CxO Seminars

Participants

Jose Murillo - Chief Analytics Officer, Banorte

Introduction to Data Science in Python

09:00 - 13:00Lounge 3: AI Academy - Training Sessions

Course Description

This hands-on half-day workshop is designed for datascience/machine learning beginners and will set thefoundations for a career or further learning for moreadvanced topics in data science.

With the guidance of Rick Copeland – python expertwith over 20 years training g experience, this coursewill familiarize you with the core Python data sciencetools including Jupyter, Numpy, Pandas Matplotlib, andScipy – enabling you to start your journey into theworld of data science.

If looking to further focus your abilities in data science,this course can be complimented with ‘Introduction toMachine Learning’, which will continue in theafternoon.

Why this course?

• Hands-on training – This course will introduce datascience tools and set the foundations for your startin data science.

• Experienced trainer – You will be instructed byauthor and consultant, Rick Copeland, who has 20+years industry and training experience.

• Inclusion of online course, Introduction to PythonProgramming – To prepare you for the workshopyou will have access to our online course.

• Data science and machine learning book included– Included in the package is a comprehensive bookon mathematical and statistical methods for datascience and machine learning that will promotefurther learning after the course.

•

Price: $499

Price: $799 (combined with Introduction to MachineLearning)

Outline

• What is data science and introduction to Jupyternotebook

• Python numerical processing•

◦ Why is Python bad for number crunching◦ Numpy for performance◦ Slicing and dicing numpy arrays

• Pandas for data munging•

◦ Pandas Series and DataFrame objects◦ Getting data into / out of Pandas◦ Filtering, concatenating, and merging

DataFrames◦ Grouping DataFrames

• Matplotlib for visualization•

◦ Figures, axes, plots, and subplots◦ Integration with Pandas

• Scipy for scientific computing (as time permits)•

◦ Scipy.stats and random variables◦ Demo of Scikit-Learn for ML

Participants

Rick Copeland - Python Programming Expert andInnovation Academy Trainer, Instructor, Entrepreneurand Developer

Opening Keynote: Evolving a global institutionaround AI - A conversation with Lori Beer


Participants

Lori Beer - Global Chief Information Officer, JPMorganChase

Chairperson's Welcome

09:40 - 09:504) AI Finance Summit

Participants

Yue Malan - Senior Research Analyst, Aite Group

AI meets AR - Supercharging model buildingand validation for regulatory compliance


Senior Representative, IBM

Participants

Seth Dobrin - Vice President and Chief Data Officer,IBM Watson

Welcome from Chair and Intro


Participants

Salvatore Salamone - Editor in Chief, RT Insights

Harnessing Data to Identify Opportunities &Inform Personalization


Participants

Neil Sanyal - Global Head of Research DigitalMarketing, Morgan Stanley

Chairperson's Welcome

09:50 - 10:005) AI Retail Summit

SESSIONSDAY 1 - 11/12/2019

AI Summit New York11-12 December 2019

Javits CenterNew York

tmt.knect365.com/ai-summit-ny/

AI for the Online Travel Marketplace: Platformsand Solutions


As the world travel platform, Expedia Group helpsknocking down the barriers to travel, making it easier,more enjoyable, more attainable and more accessible.We are taking the AI-First approach to bring the worldwithin reach for customers and partners around theglobe. We built our own scalable, performing AIplatform to support fast adoption and innovation of AI-First solutions for all our brands, partners, andsuppliers. We have built unique expertise in AI forTravel in Deep Learning, NLU/NLP, Computer Vision,and many more areas. We executed with speed andprecision to deliver the AI-First travel experience.

Participants

Luyuan Fang - Head of AI Lab - VP Technology,Expedia Group

Welcome and Introduction to AI Summit andNYAI


Participants

Maryam Farooq - Founder and Director, NYAI

How Target is Using AI to Modernize its SupplyChain


State-of-the-art AI is helping Target build a supplychain that’s faster, smarter and more efficient – tobetter serve guests shopping in store, online or on thego. Target’s Chief Data and Analytics Officer ParitoshDesai will discuss:

• How technology, new processes and dataoptimization has enabled Target’s stores-as-hubmodel

• How AI is transforming inventory managementintelligence

• How predictive analytics is playing a growing rolein store replenishment.

Participants

Paritosh Desai - Chief Data and Analytics Officer,Target

The past and future of AI in the Department ofEnergy


Participants

Rick Perry - Secretary of Energy, United StatesGovernment

Leverage AI & Automation to build a CognitiveConnected Financial Services Enterprise


This session will explore the following:

• Why is a Cognitive Connected Financial Enterpriseimportant today?

• Generating insights across the customer journey.• Proven case studies and real examples of financial

enterprises solving business challenges through AIand automation.

Participants

Praveen Kombial - Global Product Head - BusinessApplications, EdgeVerve

Navigating the Practical Challenges of MakingAI Real – Data Integration, Data QualityAssurance and Model Implementation


While the sci-fi-sounding AI scenarios highlight thetechnology’s incredible computational power, thepractical, effective applications begin with data. –Forbes.com. To make AI real, organizations face threepractical challenges:

1. Integrating data across multiple sources2. Resolving data quality issues3. Implementing machine learning models quickly

and efficiently

The presentation will focus on the approach ofaddressing these concerns to reduce time to marketand enhance ROI of AI initiatives.

Participants

Hindol Basu - CEO, Actify Data Labs

From Chatbot to Conversational Excellence


Customer expectations are changing fast.Conversational platforms will change the way humansinteract with technology in the future. ArtificialSolutions believes that people should be able tointeract with technology intelligently, using their ownvoice, in their own terminology and across whateverchannel they choose. Andy Peart, CMSO of ArtificialSolutions, will present the 5 key ideas that makeConversational AI radically different from chatbots.

Participants

Andy Peart - Chief Marketing and Strategy Officer,Artificial Solutions

Beauty AI 360: Mastering AI for Consumer-Centric Solutions


Perfect Corp. founder and CEO, Alice Chang, will diveinto the evolving consumer-centric strategy necessaryin today’s competitive landscape. She will spotlight theadvanced AI and AR technology helping beauty brandsand retailers connect with their customers throughtailored, interactive, personalized experiences thatdrive conversions. Live onsite demos will showcasesuccessful use cases illustrating how brands areleveraging YouCam AI and AR beauty tech acrossomni-channel touchpoints to meet the demand for aconsumer-centric approach.

Participants

Alice Chang - CEO & Founder, PerfectCorp

Embrace the Future of Work - an IBMPerspective


Participants

Jim Casey - Director - Digital Business Automation,IBM

AI Opportunity Audit - Roadmapping Session

10:30 - 11:30Lounge 2: AI Implementation Studio - Workshops

There is Nothing Artificial About ArtificialIntelligence - What’s Real, What’s Hype andHow to Get Going?


Participants

Jeff McMillan - Chief Analytics and Data Officer,Morgan Stanley





Managing AI Research Projects


1. Intro

2. What makes AI projects management different fromgeneral SW projects management

3. Data

4. Research process

5. People

Participants

Mihail Sirotenko - Team Lead - Senior AppliedResearcher, GoogleAI, Google

Improving the Future of Work throughEnhanced Digital Intelligence


Automation has been facing serious roadblocks. Themost common are process bottlenecks and lack oftransparency, inability of systems to analyzeunstructured information and low scalability. ABBYY’schief innovation officer Anthony Macciola will tell howthese long-standing pain points can be resolved withthe help of Artificial Intelligence. ABBYY’s AI gives thenew digital workforce the skills to understandenterprise content and processes. We call this DigitalIntelligence for the enterprise.

Participants

Anthony Macciola - Chief Innovation Officer, ABBYY

Morning Networking Break


The Future of AI in Retail: Insights From theWalmart Intelligent Retail Lab


A review of the current state of AI in retail, how we gothere, and where we’re going. What are the coretechnologies, tools, and business decisions facingretailers, and how is Walmart addressing them with itsIntelligent Retail Lab?

Participants

Jason Nichols - Director of AI, Intelligent Retail Lab,Walmart

Racing ahead with Artificial Intelligence


Participants

Armen Kherlopian - Chief Science Officer, Genpact

Investment Strategies - Identifying EmergingLow-Risk / High Return Use Cases inAutomation and AI


Participants

Thomas Vincent - Senior Director, Head of DataScience, Getty Images

Comcast's Deep Dive into The World of AI


In this talk we will describe how Comcast uses AI andMachine Learning in many of its products from theEmmy winning voice remote and content discoveryalgorithms, to using media analytics to create a betterexperience for our customers in the home on the X1entertainment system. We will also talk about a majorrecent effort by Comcast to improve the customerservice experience for its customers with virtualassistants and reinforcement learning.

Participants

Jan Neuman - Senior Director - Applied AI Research,Comcast

Delivering a Focused Strategy on Impactful,Actionable, and Scalable AI Technologies inthe Insurance Industry


In the insurance industry, AI is transforming areas suchas underwriting, customer service, claims, marketingand fraud detection. This session will be exploring howto develop a strategy to harness businessopportunities by leveraging AI. The path from concept,evangelization, strategy to execution for a use case atEverest Re will be discussed.

Participants

Sumeet Maheshwari - VP, Reinsurance IT, Everest Re

Morning networking break






Transforming Financial Services through RPAand Intelligent Automation


The overwhelming majority of financial institutions stillheavily rely on manual processes, which tend to beinefficient, costly and increase the probability of errorsand fraud.

The good news is that over 25% of Financial Servicesbusiness processes are likely to be automated in thenext few years. Implementing Robotic ProcessAutomation (RPA) with cognitive intelligence is acritical tool to help Organizations automate manualrepetitive activities, access unstructured data, andquickly deliver error-free results.

In this session, Automation Anywhere will offerinsights on how banks have successfully implementedRPA. You will hear about:

• How RPA technology is evolving and where is itbeing used

• RPA and cognitive intelligence solutions trends inFinancial services

• Example RPA use cases in Financial Services

Participants

Steven Gold - Global Industry Leader - FinancialServices, Automation Anywhere







Panel - The AI Ecosystem Imperative


Deloitte, together with a panel of industry, startup,academic, and government representatives, willexplore the importance of engaging the entireecosystem of partners in order to enable yourorganization’s AI success.

Participants

Sheryl Jacobson - Strategy and TransformationLeader, Deloitte Consulting

Gauthier Vasseur - Executive Director - CEO andFounder, Berkeley Fisher Center

Rachel Trombetta - Software Director, GE Digital

Igor Taber - SVP of Corporate Development andStrategy, DataRobot

Using AI to Drive Revenue Across the RetailIndustry


The retail industry is embracing AI in a variety of ways.Attend this session to:

• Identify the key drivers of AI in the retailenvironment, and assess the potential barriers toadoption

• Learn about the top use cases for AI in retail, andhow they’re being applied in a real-worldenvironment by retailers

• Hear about the key vendors in the space, and howthey’re working with retailers to deliver real-worldROI from retail AI implementations

Participants

Keith Kirkpatrick - Principal Analyst, Tractica

Training and Deploying Classification Modelswith AutoML


Participants

Paul Ganssle - Senior Software Engineer, Google

Peter Grabowski - Software Engineering Manager,Google

Real World Success Stories to Help YouPrepare and Scale AI


The deployment of AI has tripled in the past year, butmany organizations struggle to scale AI beyond aninitial use case. Join us to learn more aboutstrategically preparing for AI adoption to provide initialvalue as well as prepare for scale. We will walkthrough a strategic approach to AI adoption, leveragingseveral real-world examples pertinent to FinancialServices organizations.

Participants

Christine Livingston - Chief Strategist and PracticeDirector, Artificial Intelligence, Perficient

Innovating The Future of AI-enabledAutonomous Flight with Lockheed Martin


Participants

Robie Samanta Roy - Vice President, Technology,Lockheed Martin Government Affairs

Panel: AI and ML Enabled Speech Technology -Exploring The Latest Disruptions in The Spaceand Their Implications for Users


Current AI and machine learning (ML) technologies arestarting to change the way we build and innovate.However, the power of our current ML technologies isnot fixed. This panel discussion will explore where MLis at the moment and where it is heading in the next 10years. How are its current uses cases different fromthose we can expect to see in the future? How willincreased technological leverage change how we dobusiness? This panel will explore these themes andtheir impact on the application of speech technology(ASR).

Participants

Mark Beccue - Principal Analyst, Tractica

Sam Ringer - Machine Learning Engineer,Speechmatics

James Lyle - Director, Custom Linguistic Solution,Appen

Laura Horvath - Director of Product Marketing, FigureEight, an Appen Company

Nandhu Nandhakumar - Senior Vice President,Advanced Technology, LG Technology Centre ofAmerica

Claire Mitchell - Director, Innovation, VaynerMedia

Fireside Chat: Hyperpersonalizing theCustomer Experience with Conversational AI


Participants

Sunny Parikh - Vice President and Co-Head, FinTechInnovation Lab NY, Partnership Fund for New York City

Deep Learning for Retail Innovation at Sears


Highlights:

• Applying Deep Reinforcement Learning ( AlphaGo)to plan best moves for long term gains. Applied toInventory/Procurement, Marketing. Coupons.

• Applying Generative Adversarial Neural Networksfor AI generated best selling Footwear for RetailPrivate Labels.

• AI based Anomaly detection applied to Sales,Procurement Fraud Detection

• AI based Store Simulators to test out various storestrategies before deploying in real life.

Participants

Srini Kandala - Head, Innovation and Sears DeepLearning Center, Sears

AI: Cyber defense or cyber-threat?


Participants

Justin Fier - Director for Cyber Intelligence & Analytics,Darktrace

Top 3 Lessons Learned Deploying Real-WorldAI


While Artificial Intelligence (AI) is fueling amazinginnovation in many industries, deep learning andvarious related technologies remain a giant mysteryfor most looking to get started. At Pure, we helpedbuild and deploy some of the most advancedinfrastructures for AI, including powerful AIsupercomputers to systems for customers across usecases, including healthcare, financial services, andautonomous vehicles.

In this session, we will share the top three lessonslearned in making AI initiatives successful in real-worlddeployments.

Participants

Ramnath Sai Sager - AI Product and Solutions Lead,Pure Storage





The Maker Mindset: Simplifying Decisions byDoing


For most organizations the hardest part of AI isunderstanding how we can harness it for our business.Let's look at how we might structure decisions tomake the most of the data we have right now whilelaying the groundwork for the future.

Participants

Ryan Kee - Director - Innovation, AI, Walmart

Efficient Data Labeling for AI


Data is the power behind Machine Learningalgorithms. In an era where data is ever moreabundant, the applications of Machine Learning alsoare growing exponentially.

Currently, the most successful paradigm for training isSupervised Learning—which requires labeled data.While data acquisition is not a problem, given themyriad ways we interact with and create data, labelingthat data with the quality required for these algorithmsto perform is very challenging. Complexity, time,money, and available workforce all impact datalabeling quality. Suddenly, getting the right databecomes the most important part of building AI.

To minimize the challenges of data labeling, we needto label faster, cheaper and smarter. We'll look at threeapproaches to consider: a combination of MachineLearning and Human in the loop; techniques likeTransfer Learning; and strategies like Active Learning.

Participants

Aristotelis Kostopoulos - Vice President, ProductSolutions, AI, Lionbridge Technologies

5 Worst Practices for AI / ML Deployments –And How to Avoid Them


Enterprise organizations in every industry are adoptingmodern, advanced analytical techniques using AI andMachine Learning (ML) for a variety of different usecases. However, many of these enterprises arestruggling to operationalize these AI / MLenvironments for large-scale deployments across theirdata science and analyst teams. That’s because theyoften implement anti-patterns or “worst practices” thatultimately trip up those deployments. In this session,we’ll explore the most common anti-patterns and howto avoid them – while designing a strategy of bestpractices for AI / ML in the enterprise.

Participants

Matt Maccaux - Global Field CTO, HPE BlueData

The emerging distributed application platformfor AI-assisted business


Where Digital Transformation meets LoB evolution

What is the case for instrumentation

Who is successful at unlocking new business valueusing AI-assisted operations

Participants

Geng Lin - EVP & CTO, F5 Networks

Using AI and Blockchain to Monetize theMobile Economy


Consumers create a data trail by tapping their phones;businesses can tap into this trail to harness the powerof the three trillion dollar mobile economy. This two-way exchange benefits both customers andbusinesses. In this talk, Dr. Ghose will discuss howBlockchain, AI and mobile technologies are being usedby firms to monetize the digital economy.

Drawing from his best selling and award winning book,TAP: Unlocking The Mobile Economy, that paints hiswork in the US, Europe, and Asia, with companiesincluding Alibaba, Apple, China Mobile, CBS, NBC,Facebook, SK Telecom, Samsung, Snapchat, andTravelocity, he will identify the nine forces that shapeconsumer behavior, including location, context, time,crowdedness, trajectory, and weather, and examinehow these forces operate, separately and incombination to enable retailers and conveniencestores target consumers with mobile ads, couponsand offers.

When mobile advertising is done well, the smartphoneplays the role of a personal concierge―a butler, not astalker. This talk will highlight the true influence mobilewields over shoppers, and the lucrative opportunities itrepresents. In a world where Blockchain is being usedto tackle digital ad fraud, the future of the mobileeconomy seems limitless.

Participants

Anindya Ghose - Heinz Riehl Chair Professor ofBusiness at Stern School of Business, New YorkUniversity

Lunch break and opportunity to visit the expo






Intelligent Finance: Searching for Success inFinancial Services


Financial institutions need information, not data. Onaverage, financial employees waste a day a weeksearching across silos, systems, and clouds forinformation. It's pre-digital-age work. Attend thissession to learn how AI-Powered Search gives youremployees the information and intelligence they need.

This session will help you understand new, low-disruption approaches to use cases across investmentmanagement and retail banking,

Attend this session to hear how financial institutionscan use AI-Powered Search to:

• Rethink competitive survival and success.• Learn how one of our customers saves over $21

million per year with our platform.• Implement a unified platform to support multiple

use cases across sales, service, transformation,investment research, M&A, and new products.

• Maximize value from all your data. External andinternal. Structured and unstructured.

Participants

John Finneran - Product Marketing Lead, FinancialServices, Sinequa

Networking Lunch


Workshop: 5 Habits of Highly ProductiveCompanies - Exploring AI, Innovation andHappiness


“What makes a company productive? We will explorehow innovation, creativity and the latest technologicaladvances help foster faster and lasting changes in thisarea.

Did you know that if employees are happy, theirproductivity raises significantly? This workshop alsofocuses on how corporations can use the latestresearch in happiness and employee satisfaction tosupport productivity and growth.

Format: presentation, discussion.

Bonus: relaxation techniques and habits of happiness– tips from around the world.”

Participants

Julia Benz - Office of The CIO, Ford Motor Company







The future of AI in China


Participants

Chua Kong Ho - Technology Editor, South ChinaMorning Post

Chair's Opening Remarks


Participants

Karen Bhatia - Senior Vice President, New York CityEconomic Development Corporation

How Shopify Leverages Data and ML to Power1M+ Merchants


• Overview of the data and the data platformevolution at Shopify

• How ML is applied at Shopify• Exploring use cases (fraud detection,

recommendations, etc.)

Participants

Xinyi Zhao - Technical Product Lead, Shopify

Business Leaders' Essential AI MarketOverview with Tractica - Q4 Forecast Update &2020 Outlook


Participants

Aditya Kaul - Research Director, Tractica

Keith Kirkpatrick - Principal Analyst, Tractica

Introduction to Machine Learning


Course Description

Machine learning is a subset of artificial intelligence(AI) that provides systems with the ability to learn andimprove from experience, without a need for explicitinstructions. While a simple concept, machine learninghas opened a world of possibilities and today it beingused across various industries for a multitude offunctions whether this be improving customerexperiences through making personalisedrecommendations to predicting future values of astock price.

This half-day workshop is designed for data science/machine learning beginners and will walk you throughmachine learning concepts with SciKit-Learn, a full-featured machine learning toolkit for Python.

Depending on your level, this course can becomplimented with, ‘Introduction to Data Science’ thatwill be held in the morning.

Why this course?

• Hands-on training – This course will providepractical guidance on SciKit-Learn and machinelearning models

• Experienced trainer – You will be instructed byauthor and consultant, Rick Copeland, who has 20+years industry and training experience.

• Inclusion of online course, Introduction to PythonProgramming – To prepare you for the workshopyou will have access to our online

• Data science and machine learning book included– Included in the package is a comprehensive bookon mathematical and statistical methods for datascience and machine learning that will promotefurther learning after the course.

•

Price: $499

Price: $799 (combined with Introduction to DataScience)

Outline

• Introduction to Machine Learning•

◦ Supervised vs unsupervised learning◦ Regression vs classification◦ Performance: the bias/variance trade-off

• Survey of ML Models in Scikit-Learn•

◦ Linear models◦ Trees & forests◦ K-nearest neighbors◦ K-means clustering

• Preprocessing data for ML models•

◦ Feature engineering and selection◦ Feature scaling◦ Principal component analysis

• Evaluating ML models•

◦ Accuracy, precision, and recall◦ Test/train/validate splits





◦ Cross-validation

Participants

Rick Copeland - Python Programming Expert andInnovation Academy Trainer, Instructor, Entrepreneurand Developer

Building an AI Engine Your Customers CanTrust


Gravity is unforgiving and missions cannot fail; this isa story of how AI delivers success in aircraft readinessand maintenance when failure is not an option.

Lockheed Martin’s journey to creating an AI processthat fosters repeatability, smarter automation, andcost savings. By minimizing the risk of failure andcreating repeatable incremental successes, there isnow a foundation of trust in the output of AI that helpsmeet stringent customer standards and companyfinancial goals.

Using SAS AI provides the edge to focus resourceswhere they are needed most – on fulfilling criticalmissions.

Participants

Lonnie Miller - Principal Industry Consultant, SAS

Mike Isbill - Fellow/Data Analytics, Air Mobility andMaritime Missions, Lockheed Martin

Smarter Enterprises Built on AI


Participants

Atul Soneja - Global Head, EdgeVerve

Kubeflow Pipelines - Speeding Up TheDevelopment Cycle for New Models andSimplifying Deployments of Models toProduction


• Speeding up the development cycle for newmodels with Kubeflow pipelines.

• Offering visibility and debuggability into machinelearning pipelines.

• Simplifying deployments of models to production.

Participants

Ammar Naqvi - Product Manager for Kubeflow,Canonical

Kenneth Koski - Machine Learning Engineer, Canonical

The Who Behind AI - Methodologies for TheProduct Managing of AI Products in LegacyFinancial Services Companies


Participants

Ehsan Yousefzadeh - AI Product Manager, AIG

WorkFusion Enterprise Success: NY-Presbyterian’s Use of Intelligent AutomationImproves Patient & Employee Experiences


Hear how NY-Presbyterian's journey into Intelligentautomation positively affected a number of areas ofstrategic priority, including patient care, jobsatisfaction, productivity and an increased capacity tohandle an ever-expanding workload.

Participants

Vishal Sheth - Director of Transformation, New YorkPresbyterian Hospital

Applied Science and Intelligence at Staples’eCommerce & Retail


This talk will cover:

• How data and decision science is being applied inthe eCommerce & Retail industry

• What is Staples' approach• Potential new frontiers for intelligent applications

Participants

Nitin Verma - VP, Digital Solutions, Staples

Practical ML in DevOps: An example from AFinancial Technology Company...


Most of the FinTech enterprises need to comply withstricter data privacy laws and internal complianceregulations and end up not taking advantage of thewealth of operations information that can begenerated if cross divisional data sets are synthesized.Brown field migration of the data assets into AWSSage Maker or Azure ML or Google ML is easier saidthan done for the Financial firms due to competingregulations and data privacy rules.

We shall present an effective internal mechanism toconnect the front-to-back operations chain to providebetter DevOps solutions that are based on DataSciences and Machine Learning. Most importantly,how reasonable it is for the enthusiasts to build alearning model and apply both reinforced learningtechniques and transfer learning techniques to maketheir ML models more intelligent and adaptive forbetter Devops..

Participants

Murali Nandigama - Director of Engineering, BarclaysInternational

Proactive Compliance Risk Management &Investigations - Powered by AI


The session will cover how organizations can leveragethe power of AI to move from reactive compliancemonitoring to transform towards proactive, efficientand timely identification of compliance and regulatoryissues – thereby reducing the potential impact ofreputational, harm and financial liability. Developingand executing on an AI strategy can help organizationsbroaden their coverage of issues and deploy theirworkforce more effectively on higher value activities.

Participants

Satish Lalchand - Principal, Deloitte Risk and FinancialAdvisory

Securing Your Enterprise - Leveraging ML forThreat Detection and Multi-Layer Security - AISecurity Strategy Workshop + Demo


Participants

Justin Fier - Director for Cyber Intelligence & Analytics,Darktrace





Anticipatory Banking: Using AI to CreateAdvantage in a Digital World


In today’s digital world, customers expect businessesto understand their needs. While this may sometimessound like an exercise in clairvoyance, the truth is thatmany customers don’t say what they want. By using AIand machine learning to gather and analyzebehavioral, social and transactional data, it is possiblefor organizations to develop a far deeper, morepersonal understanding of their customer, thusaddressing their unique needs in a personal andrelevant way. In this talk by Rashed Haq, PublicisSapient’s global head of artificial intelligence, roboticsand data, will explore practical applications for AI andchallenges addressed bridge the gap betweenexpectation and fulfilment.

Participants

Rashed Haq - Global Head of AI, Robotics & Data,Publicis Sapient

Sustainability and Profitability Through AI inThe Supply Chain


Participants

Andreas Schmidt - Product Director, Blue YonderGmbH, A JDA Company

Real Time Event Detection on Social MediaStreams


Social networks are quickly becoming the primarymedium for discussing what is happening around real-world events. The information that is generated onsocial platforms like Twitter can produce rich datastreams for immediate insights into ongoing mattersand the conversations around them.

To tackle the problem of event detection, we modelevents as a list of clusters of trending entities overtime.

We describe a real-time system for discovering eventsthat is modular in design and novel in scale and speed:it applies clustering on a large stream with millions ofentities per minute and produces a dynamicallyupdated set of events. In order to assess clusteringmethodologies, we build an evaluation dataset derivedfrom a snapshot of the full Twitter Firehose andpropose novel metrics for measuring clusteringquality. Through experiments and system profiling, wehighlight key results from offline and online pipelines.

Finally, we visualize a high profile event on Twitter toshow the importance of modeling the evolution ofevents, especially those detected from social datastreams.

Participants

Ashish Bansal - Senior Engineering Manager, ML(Recommendations), Twitter

Samir Chainani - Senior Software Engineer, Twitter

Weaving Artificial Intelligence into EnterpriseProduct Strategy


This session will explore how Moody's MachineLearning team created ML FabricTM to enable rapidprototyping and go-live for Artificial Intelligence &Machine Learning products. The team will share howtheir framework enabled the development of new AIsolutions for automated spreading (Moody’sQUIQspread TM) and automated compliance riskassessment (Moody’s Adverse Media).

Participants

Ashit Talukder - Head of Machine Learning, Moody'sAnalytics Accelerator, Moody's

Rupinder Khandpur - Director of Software Architecture,Moody's Analytics Accelerator, Moody's

Optimizing Multichannel Self-Help Experiencesfor Customers


Participants

Speaker TBA , Agara

Accelerating the AI Journey Through OpenInnovation


From artificial intelligence to the Internet of Things,companies are connecting the physical world to thefast-changing digital world. This shift towards digitaltransformation can create roadblocks for manycompanies. Open Innovation can help companies thatwant to move beyond ideas to actually extending theircore business into new markets. Open Innovationinvolves drawing on global resources and working withexternal partners to fill in gaps and accomplish mutualgoals. During this TED-like presentation, Dr. TolgaKurtoglu will provide best practices and tangibleexamples of how Open Innovation can accelerateorganizations’ AI journey.

Participants

Tolga Kurtoglu - President, PARC, a Xerox Company

AI at Enterprise Scale - The Four Dimensionsof Sustainable Success


This presentation will give you a pragmatic, tested, andeffective framework for overcoming some of the mostcommon AI roadblocks and for speeding up valuecreation, creating alignment across diversestakeholders and delivering differentiated AI solutions.This comprehensive approach ensures success wellbeyond pure model performance and takes intoaccount the complex regulatory, technical and politicalchallenges of AI at enterprise scale.

Participants

Bjorn Austraat - SVP, AI Enterprise Solutions - Agile AI,Wells Fargo





Value Delivery in AI: Roadmapping MachineLearning Products vs. Traditional Software


“What’s the value?”

This is one of the most dreaded phrases to hear fromleadership after months of hard work.

Unlike software development, the incremental deliveryof a machine learning project can be harder forbusiness leaders, partners and stakeholders to grasp.With more investment going into this space, growingteam sizes, and increasingly complex problems tosolve, the need for quality product management in AIhas increased in recent years to ensure theseinvestments are creating the most value. The resulthas been the need for a more robust approach whichbrings together the best of product management withthe needs of more hypothesis-driven teams.

Whether you are a tech partner, researcher, businessleader or in a product role today, this session willhighlight tactics to improve alignment, roadmapping,and continuous delivery of AI projects across yourorganization.

Participants

Trevor Gurgick - Product Manager - Machine Learningand Data Science, Audible, Inc

Leveling up Artificial Intelligence: ArchitectingTeams That Operate and Prioritize Efficiently


Serkan will be sharing his experience and insights onthe different levels of Artificial Intelligence thatcompanies go through. From when a company is juststarting from scratch and evaluating AI technologyand infrastructure, to AI mature companies who haveinstitutionalized AI transformation within theirorganization. Walking through the different levels of AImaturity within a company, showing what companiescan do to move to the next level, and architect teamsthat operate and prioritize efficiently.

Participants

Serkan Piantino - CEO & Founder, Spell

Measuring Incremental Value of a businessusing Machine Learning Algorithms -CastleGate Wayfair Case Study


Wayfair launched the CastleGate program, a leadingdrop-ship operation in 2014, helping 300+ suppliersboost sales by delivering products to customers faster,safer, and at a lower cost than ever before. As weexpand our supplier partnership footprint inCastleGate, it’s critical for us to quantify incrementaldollar impact of entering a product in the program,which translates into a challenge for analytics inabsence of historical experimental design. In thissession, learn how we leveraged multiple machinelearning algorithms on top of Bayesian time seriesforecasting to gauge incremental value of CastleGate.

Participants

Ankit Mangal - Associate Director, Web Analytics,Wayfair

ICED(AI) Fireside Chat: AI in AssetManagement


Participants

Lloyd Danzig - Chairman & Founder, ICED(AI)

Andrew Dassori - Founding Partner & Chief InvestmentOfficer, Wavelength Capital Management

Enterprise ML - Breaking Through the Wall toProduction


Imagine a business where every process, product andexperience is instrumented to capture data forcontinuous analysis and automated, intelligentresponse. While born-on-data disruptors build theirbusinesses based on these capabilities, traditionalenterprises are finding they must embrace, adopt andtransform around them.

And while corporate AI initiatives are fuelinginvestment in new technologies and skills profiles,organizations are finding it’s not enough.Operationalizing machine learning requires building aculture and operating environment for experimentationand continuous learning across the ML developmentlifecycle at scale.

We’ll address the cultural and technological barriers totransferring machine learning from research tobusiness results and how leading enterprises areforging ahead.

Participants

Mick Hollison - Chief Marketing Officer, Cloudera

Lessons Learned to Get The Most Return onYour AI Initiatives


Gannett | USA TODAY NETWORK is at the forefront ofdigital media reaching an audience of over 140Mmonthly, and brings together local communities andbusinesses.

Kris Barton, Chief Product Officer at Gannett | USATODAY NETWORK, will speak on the company’ssuccesses using AI in its approach to its digitalmarketing solutions platform, LOCALiQ. Kris will sharehow he leads a team that innovates with AI to createand continue the evolution of a stronger set ofmarketing solutions for our clients. This session willexplore the lessons Gannett has learned in deployingAI and how businesses can expand their ROI throughthe use of AI.

Participants

Kris Barton - Chief Product Officer, USA TodayNetwork

Using Data Science Insights to Help UsersChallenge The Status Quo of Decision Making


Participants

Kayla Brizo - Lead Product Manager - Data & Analytics,Sony Music Entertainment

Afternoon Networking Break


Chairperson's Closing Remarks


Afternoon networking break










AI in Insurance: Modelling the Value of Risk


Participants

Boyi Xie - Head Modelling & Insights Americas, VP,Swiss Re

Building and Scaling AI Capabilities Across theOil and Gas Value Chain


The O&G industry has always been a technology drivenindustry. Opportunities for artificial intelligence areendless, with applications spanning the entire valuechain, from evaluating seismic and wellhead data tooptimizing manufacturing.

But adopting and scaling new digital technologies canbe challenging for multiple reasons. Additionally, theemphasis on safe and reliable operations raises otherconsiderations that are unique to the O&G sector.

Participants

Sarah Karthigan - Global AI Executive - Data ScienceManager, ExxonMobil

Machine Learning for Software Testing


Participants

Elena Treshcheva - Business Development Manager,Researcher, Exactpro Systems

Can AI Help to Close the Gender Equity Gap?


Participants

Katica Roy - CEO, Pipeline Equity

Similarity in Machine Learning and AI


Similarity measures are the driving force for nearlyevery machine learning algorithm and AI driventechnology.

From cleaning customer information, to rankingproduct recommendations, to identifying audiences,the application of machine learning and AI in mediaand entertainment are limitless.

The latest technologies offers users the ability toimplement these algorithms faster than ever, butselecting the right measurement can impact theperformance, accuracy and scalability of any model.

In this talk, you will learn how similarity can bequantified using different measures and applied to fitthe data, the model and the business objective.

Participants

Jennifer Shin - Product Director, Contextual andAdjunct Assistant Professor at NYU Stern School ofBusiness, NBCUniversal Media

Panel: Optimizing Legacy IT Architecture toFacilitate Implementation of AI in The FinancialServices Sector


• Examining the short term effectiveness and long-term potential of start-up vendor partnerships

• Enhancing service offering through insights gainedas a result of Machine Learning Implementation

• When should you work with pure-play technologyproviders, and when should you look to tier 1consultancies?

• What are the “low hanging fruits” for heads of IT tolook out for when identifying new use cases acrosstheir stack?

• Handling sensitive data and responsible movementof data across platforms during IT overhaul

Participants

Will Thompson - VP and Managing Director, ThoughtLeadership, Forbes

Yue Malan - Senior Research Analyst, Aite Group

Andy Mahdavi - Chief Data Science Officer, States Title

Vignesh Iyer - Global Vice President - EmergingTechnology, Winjit

Anurag Setty - Lead Data Scientist, Barclays US

The Business Outline for AI & BOT Deployment


1. Pilot Summarize why building a pilot is ideal. Howto best to pilot new concepts, including size,duration, and expectations

2. Scale & Training Outline approach to scaling up(slow vs rapid), communication and expectationmanagement, and mindset approach to handlingthese new concepts (AI/BOT). Describe approachto training; hands on, web vs f2f, check in postlaunch

3. Change management How to utilize changemanagement to support new “tools”, embracefailing, and driving new way of working

Participants

James Bongi - Head of Strategy and Operations forArtificial Intelligence, Novartis

Making Commerce Smarter with AI


Participants

Joey Freund - Data Developer Manager, Shopify

How will AI intersect with the othertechnologies in your roadmap?


Participants

Ron Bodkin - Technical Director, Applied ArtificialIntelligence, Google





The Future of AI for Good - IBM Watson AIXPRIZE


XPRIZE runs large-scale incentivized competitions toenable breakthroughs and accelerate the future. Theinitial Ansari XPRIZE helped launch today’s privatespace industry and over the last 20 years XPRIZE hasrun & awarded prizes in ocean mapping, education,and transforming carbon emissions. Since 2016XPRIZE has operated the IBM Watson AI XPRIZEcompetition. This is a $5 million global competitionchallenging teams to apply AI (ML, DL, NLP, etc.) todifferent challenges facing humanity.

This particular panel talk will feature three of thecompeting organizations in the competition – ElementInc, emPrize, and Aifred Health. The discussion willfocus on the AI for Good movement (and it’s futurepotential), the challenges around AI for Good (e.g. datainclusivity, structured data for solving grandchallenges), and what it takes to operate a company inthis new space. In short - this panel will help theaudience understand how AI for Good and theseparticular solutions (from the companies) can build abetter future state through human + machinecollaboration.

Participants

Moderator: Devin Krotman - Director of the IBMWatson XPRIZE, XPRIZE

Rebecca Distler - Director, Global Health Initiatives,Element Inc

Ashok K. Goel - Professor, Interactive Computing &Chief Scientist, C21U, Georgia Institute of Technology

David Benrimoh - Chief Science Officer, Aifred Health

A Data-Sharing Model To Accelerate theImplementation of AI in Pharma


Pharmaceutical companies generate large internaldatasets across R&D and Operations that can beleveraged to develop or further new AI and MLsolutions. In addition, companies have access to realworld data sets, such as electronic medical records,claims, and genomic data.

However, today’s data-sharing model for allowingpotential collaborators to access this internal data,which is sensitive or proprietary, is often cumbersomeand legally restrictive. This inability to easily sharedata prohibits pharmaceutical companies fromsignificantly scaling collaboration and developmentwith external partners. A more nimble and streamlinedapproach to sharing data with an external network ofcollaborators is needed to speed AI development andadoption in pharma.

To address this, Pfizer developed its DigitalAccelerator that serves as a rapid testing environmentfor internal and external collaboration supportingbusiness innovation across the company. This talk willdetail how Pfizer is delivering an incubation frameworkto support collaborative development as well asenable and streamline the engagement and evaluationof potential AI and ML partners.

Participants

Sandeep Burugupalli - Head of the Data Center ofExcellence, Pfizer

Headline panel: The role of policy andregulation in the development of AI


Participants

Ana Ariño - Executive Vice President and ChiefStrategy Officer, New York City Economic DevelopmentCorporation

Manuel Morales - Chief Scientist, AI, National Bank ofCanada

Bob Cohen - Economist and Senior Fellow, EconomicStrategy Institute

Tim Bradley - Minister Counsellor (Industry, Science &Education), Australian Government

Mina Hanna - Co-Chair, IEEE-SA Global Initiative onEthics of AI Systems, IEEE





TIME 1) DELIVER - CXOSAND TOP-LEVEL BUSI-NESS LEADERS

2) IMPLEMENT - SE-NIOR STRATEGISTSAND HEADS OF FUNC-TION

3) DEVELOP - HEADSOF TECH AND PRACTI-TIONERS

4) AI FINANCE SUM-MIT

5) AI RETAIL SUMMIT LOUNGE 1: AI FORBESBOARDOOM - CXOSEMINARS

LOUNGE 2: AI IMPLE-MENTATION STUDIO -WORKSHOPS

LOUNGE 3: AI ACADE-MY - TRAINING SES-SIONS

09:00 09:00 - Welcome Ad-dress

09:20 - OpeningKeynote: Evolving aglobal institutionaround AI - A conver-sation with Lori Beer

09:45 - AI meets AR -Supercharging modelbuilding and valida-tion for regulatorycompliance

09:00 - Visit DeliverStage for OpeningKeynote

09:50 - Welcome fromChair and Intro

09:00 - Visit DeliverStage for OpeningKeynote

09:40 - Chairperson'sWelcome

09:50 - HarnessingData to Identify Op-portunities & InformPersonalization

09:50 - Chairperson'sWelcome

09:00 - Creating A Da-ta Literate, AI ReadyBusiness from TheTop Down

09:00 - Introduction toData Science inPython

10:00 10:10 - The past andfuture of AI in the De-partment of Energy

10:35 - There is Noth-ing Artificial About Ar-tificial Intelligence -What’s Real, What’sHype and How to GetGoing?

10:00 - AI for the On-line Travel Market-place: Platforms andSolutions

10:25 - From Chatbotto Conversational Ex-cellence

10:50 - Improving theFuture of Workthrough EnhancedDigital Intelligence

10:00 - Welcome andIntroduction to AISummit and NYAI

10:20 - Navigating thePractical Challengesof Making AI Real –Data Integration, DataQuality Assurance andModel Implementa-tion

10:45 - Managing AIResearch Projects

10:10 - Leverage AI &Automation to build aCognitive ConnectedFinancial Services En-terprise

10:30 - Embrace theFuture of Work - anIBM Perspective

10:50 - Morning Net-working Break

10:00 - How Target isUsing AI to Modernizeits Supply Chain

10:25 - Beauty AI 360:Mastering AI forConsumer-Centric So-lutions

10:50 - The Future ofAI in Retail: InsightsFrom the Walmart In-telligent Retail Lab

10:30 - AI OpportunityAudit - RoadmappingSession

SCHEDULEDAY 1 - 11/12/2019











11:00 11:00 - Racing aheadwith Artificial Intelli-gence

11:25 - Morning net-working break

11:55 - Innovating TheFuture of AI-enabledAutonomous Flightwith Lockheed Martin


11:45 - Panel - The AIEcosystem Imperative

11:10 - Comcast'sDeep Dive into TheWorld of AI


11:10 - Delivering aFocused Strategy onImpactful, Actionable,and Scalable AI Tech-nologies in the Insur-ance Industry

11:30 - TransformingFinancial Servicesthrough RPA and Intel-ligent Automation

11:50 - Real WorldSuccess Stories toHelp You Prepare andScale AI


11:45 - Using AI to Dri-ve Revenue Acrossthe Retail Industry

11:00 - InvestmentStrategies - IdentifyingEmerging Low-Risk /High Return Use Cas-es in Automation andAI

11:45 - Training andDeploying Classifica-tion Models with Au-toML

12:00 12:20 - AI: Cyber de-fense or cyber-threat?

12:45 - The emergingdistributed applicationplatform for AI-assisted business

12:30 - Top 3 LessonsLearned DeployingReal-World AI

12:55 - Using AI andBlockchain to Mone-tize the Mobile Econo-my

12:00 - Panel: AI andML Enabled SpeechTechnology - Explor-ing The Latest Disrup-tions in The Spaceand Their Implicationsfor Users

12:40 - Efficient DataLabeling for AI

12:10 - Fireside Chat:Hyperpersonalizingthe Customer Experi-ence with Conversa-tional AI

12:40 - 5 Worst Prac-tices for AI / ML De-ployments – And Howto Avoid Them

12:10 - Deep Learningfor Retail Innovationat Sears

12:35 - The MakerMindset: SimplifyingDecisions by Doing












13:00 13:10 - Lunch breakand opportunity to vis-it the expo

13:15 - Lunch breakand opportunity to vis-it the expo


13:00 - Intelligent Fi-nance: Searching forSuccess in FinancialServices


13:00 - NetworkingLunch

13:00 - Workshop: 5Habits of Highly Pro-ductive Companies -Exploring AI, Innova-tion and Happiness

14:00 14:00 - The future ofAI in China

14:10 - Smarter Enter-prises Built on AI

14:35 - AnticipatoryBanking: Using AI toCreate Advantage in aDigital World

14:05 - Building an AIEngine Your Cus-tomers Can Trust

14:25 - WorkFusionEnterprise Success:NY-Presbyterian’s Useof Intelligent Automa-tion Improves Patient& Employee Experi-ences

14:50 - Sustainabilityand ProfitabilityThrough AI in TheSupply Chain

14:00 - Chair's Open-ing Remarks

14:10 - KubeflowPipelines - SpeedingUp The DevelopmentCycle for New Modelsand Simplifying De-ployments of Modelsto Production

14:30 - Practical ML inDevOps: An examplefrom A Financial Tech-nology Company...

14:50 - Real TimeEvent Detection onSocial Media Streams

14:10 - The Who Be-hind AI - Methodolo-gies for The ProductManaging of AI Prod-ucts in Legacy Finan-cial Services Compa-nies

14:30 - ProactiveCompliance Risk Man-agement & Investiga-tions - Powered by AI

14:50 - Weaving Artifi-cial Intelligence intoEnterprise ProductStrategy

14:00 - How ShopifyLeverages Data andML to Power 1M+Merchants

14:25 - Applied Sci-ence and Intelligenceat Staples’ eCom-merce & Retail

14:50 - OptimizingMultichannel Self-Help Experiences forCustomers

14:00 - BusinessLeaders' Essential AIMarket Overview withTractica - Q4 ForecastUpdate & 2020 Out-look

14:30 - Securing YourEnterprise - Leverag-ing ML for Threat De-tection and Multi-Layer Security - AI Se-curity Strategy Work-shop + Demo

14:00 - Introduction toMachine Learning












15:00 15:00 - Acceleratingthe AI JourneyThrough Open Innova-tion

15:25 - Enterprise ML- Breaking Throughthe Wall to Production

15:50 - Afternoon net-working break

15:10 - AI at Enter-prise Scale - The FourDimensions of Sus-tainable Success

15:30 - LessonsLearned to Get TheMost Return on YourAI Initiatives


15:10 - Value Deliveryin AI: RoadmappingMachine LearningProducts vs. Tradition-al Software

15:30 - Using DataScience Insights toHelp Users ChallengeThe Status Quo of De-cision Making


15:10 - Leveling up Ar-tificial Intelligence: Ar-chitecting Teams ThatOperate and PrioritizeEfficiently

15:20 - ICED(AI) Fire-side Chat: AI in AssetManagement

15:40 - Afternoon Net-working Break

15:15 - Measuring In-cremental Value of abusiness using Ma-chine Learning Algo-rithms - CastleGateWayfair Case Study

15:40 - Chairperson'sClosing Remarks

16:00 16:30 - Can AI Help toClose the Gender Eq-uity Gap?

16:55 - How will AI in-tersect with the othertechnologies in yourroadmap?

16:25 - Building andScaling AI CapabilitiesAcross the Oil andGas Value Chain

16:45 - The BusinessOutline for AI & BOTDeployment

16:30 - Similarity inMachine Learning andAI

16:50 - Making Com-merce Smarter with AI

16:05 - AI in Insur-ance: Modelling theValue of Risk

16:25 - MachineLearning for SoftwareTesting

16:35 - Panel: Opti-mizing Legacy IT Ar-chitecture to FacilitateImplementation of AIin The Financial Ser-vices Sector












17:00 17:20 - Headline pan-el: The role of policyand regulation in thedevelopment of AI

17:05 - The Future ofAI for Good - IBM Wat-son AI XPRIZE

17:10 - A Data-Sharing Model To Ac-celerate the Imple-mentation of AI inPharma





Welcome Address


AI Business Model Reinvention Workshop


Curated in partnership with Forbes, this CxO workshopwill dive into how organisations can use designthinking and analytics to re-imagine how they generaterevenue in the age of AI!

Introduction to Natural Language Processing


Natural Language Processing (NLP) is quicklybecoming an essential skill for modern-dayorganizations to gain a competitive edge. By enablingservices from chatbots, intelligent search and questionanswering systems, NLP tools are being used to for avariety of functions from enhancing customerexperiences to detecting threats, all in all, enablingoperations to operate more effectively.

This half-day practical workshop will see Dr CarloLipizzi, Professor at Stevens Institute of Technology,guide you through NLP tools while showing you theirreal-world applications, setting solid foundations foryour pathway into the field.

Learning outcomes

• Learn and understand popular NLP workflows withinteractive examples

• Understand how to clean and handle unstructuredtext data

• Complete NLP tasks including text classification,sentiment analysis, text clustering, summarization,topic models and recommendations

Price: $499

Course Agenda

Lecture-style. Theory and use of NLP. NLP has arelevant theoretical component. In this module, weaddress this, providing an actionable theoreticalintroduction to NLP

• Introduction and overview• Key approaches to NLP• Language in our evolving society• Tools for NLP• non coding tools• Python

Interactive-style. NLP by examples and exercises. Inthis module we provide details of the most relevantNLP methods and techniques. This includes the moretraditional - but still widely used - approaches and thenew and most relevant ones. In this moduleparticipants will work hands-on on all the topics.

• Text preparation• Basic/statistical Information Extraction• Taxonomies: use and limitations• Machine Learning models• Text vectorization• Handling language subjectivity• Detecting sentiment and emotions• Supervised vs Unsupervised vs Semi-Supervised

approach to NLP• Extracting metrics from Text

Final project. This is a capstone application of all theabove. Participants will fully analyze text, extractingkey elements and prepare a report with the insightsthey extracted.

• Tool-independent capstone exercise

Participants

Carlo Lipizzi - Professor at Stevens Institute ofTechnology & Principal Investigator for SystemsEngineering Research Center, Stevens Institute ofTechnology

Making Data Science Useful


Despite the rise of data engineering and data sciencefunctions in today's corporations, leaders reportdifficulty in extracting value from data. Manyorganizations aren’t aware that they have a blindspotwith respect to their lack of data effectiveness andhiring experts doesn’t seem to help. Let’s talk abouthow you can change that!

Participants

Cassie Kozyrkov - Chief Decision Scientist, Google

Chairperson's Welcome and Intro

09:10 - 09:357) AI Sales, Marketing and CX Summit

Participants

Mark Beccue - Principal Analyst, Tractica

Chairperson's Welcome and Intro

09:20 - 09:356) AI Healthcare Summit

Participants

Shane Walker - Research and Analysis Director, IHSMarkit

Chair's Opening Remarks


Participants

Maryam Farooq - Founder and Director, NYAI

Welcome from Chair


Participants

Devika Daga - AI Practitioner and HumaneTechnologist, MOSIP





Go Global or Go Home - How to build aprofitable international AI Business.


Participants

Alex Poulis - Senior Director, AI, TransPerfect

Enrico Santus - Language Architect, MIT

Microsoft AI: Powering new Possibilities foryour Enterprise


Participants

Gina Loften - CTO - US Services, Microsoft

Humanistic Care in the Age of AI


Participants

Hassan Tetteh - Health Mission Chief, Department ofDefense

AI/ML Advances and Impacts on Sales andMarketing


Participants

Matthew Quint - Director, Center on Global BrandLeadership, Columbia Business School

NSCAI Dialogue with Industry


Participants

Christopher Rice - Director, Research and Analysis,National Security Commission on Artificial Intelligence

Advanced Clustering Techniques for AudienceSegmentation


Participants

Roberto Sanchis Ojeda - Tech Lead - Machine LearningEngineer, Spotify

How is AI extending the customer life timevalue at Banorte


Participants

Jose Murillo - Chief Analytics Officer, Banorte

Where ML Models Meet The Real World


Machine learning operations (MLOPs) is the nextfrontier for AI/ML where IT Operations, DataEngineering, and Data Science teams work together todeploy, monitor and manage machine learning projectson production environments. In this session, you willlearn about the critical components of MLOpstechnology, and how companies are using MLOps toscale up AI projects on production environmentsacross all the major cloud providers and on-premise.

Participants

Dan Darnell - Senior Director of MLOps Products,DataRobot

How to Start and Scale AI-PoweredAutomation In Life Sciences


AI and RPA are being adopted rapidly throughout theLife Sciences industries. From the top 20pharmaceutical and medical device companies, tosmall, innovative digital-health organizations, AI andRPA have become a requirement for innovation andspeed to market.

Find out how you can enable employees to work onhigher-value projects, build value for the organization,and help create stronger relationships between healthprofessionals and clients.

How do these leading organizations scale? Where dothey start? What are the key lessons they learned?

• Learn strategies and best practices to successfullyimplement automation in a Life Sciences businesswhile avoiding common mistakes

• Review key strategies, plans and benchmarks toassure your organization is on track and able toscale automation across the business

• Find out what a ‘Digital Workforce’ is – and howthey combine AI, Machine Learning and RPA -working alongside humans to boost productivityand innovation

Participants

Catherine Calarco - Senior Director, Global Leader ofIndustry Strategy for Life Sciences, AutomationAnywhere

Performance Linguistics: The Engine Driving AISuccess


If your goal is international growth, investing in digitalcontent across multiple languages matters. To pursuemass personalization, digital marketing must blendlinguistics and AI to create and optimize content. Atglobal scale, traditional approaches like A/B testingquickly encounter constraints. With PerformanceLinguistics, AI has the potential to scale at marketspeed for digital marketers using techniques like:

• Web Page Analysis• Ad conversion analysis• Search engine optimization• Social media content engagement

Participants

Smith Yewell - CEO, Welocalize

A Data-Sharing Model To Accelerate theImplementation of AI in Pharma


Predicting Content Virality to Drive SocialTraffic


To amplify referral traffic, we have to promote the rightpiece of content at the right time. We use AI-drivenmodels that predict content likely to go viral in the nearfuture to inform our content marketing on social mediaplatforms to maximize click through traffic. This hasresulted in significant growth of our social traffic forseveral of our brands.

Participants

Sriram Subramanian - Head of Data Sciences, CondeNast

Evolving from an insurer to a fintech: how willyour business evolve?


Participants

Monica Caldas - SVP and CIO, Liberty MutualInsurance





Convergent AI in Medicine – Reduce Wastes,Do No Harm, and Avoid Misdiagnosis


Participants

Stephen Wong - Chief Research Informatics Officer,Houston Methodist

AI in Marketing in the Age of Humans withMachines


Marketers can only deal with so much data about somany customers at one time. That’s why we havetraditionally lumped massive groups of people into afew composite segments. But increasingly, customersexpect to be treated as unique individuals with theirown preferences, personalities, histories andknowledge. That type of engagement simply isn’tpossible at scale when humans are making everymarketing and customer experience decision. Thisleads to an emerging irony of the modern age ofmarketing: In order for brands to achieve the levelpersonalization that today’s customers expect,marketers need to embrace human and machinecollaboration to unleash the power of With. We shouldbegin trusting artificial intelligence to handle more ofthe details of what, how and where marketingmessages get served; and apply our humanintelligence to shaping strategy, testing and tuningtactics, applying the human touch where it mattersmost, and driving rapid growth.

Participants

Alex Kelleher - CMO, Hux by Deloitte Digital

Intelligent RPA Workshop - Platform + UseCase Discovery


Automation technology is expanding beyond RPA intoAI and Intelligent Automaton, from on-premiseinstallations to the cloud, while improving its ease ofuse and time to value.

Join Automation Anywhere's workshop to experienceEnterprise A2019 - the first cloud-based intelligentautomation platform enabling RPA and AI capabilitiesin a single workflow.

We will walk you through the automation journey,starting from building your first simple bot toautomating a complex business process previouslyrequiring multiple human interventions and decisionmaking.

The flexibility of the workshop format allows us to diveas deep into product, technology, and implementationquestions as well as walk through use cases.

Participants

Brendan Sapience - Director of Sales Engineering,Cognitive Automation, Automation Anywhere

From data to deployment and back: Challengesacross the application development journey


In building intelligent applications there are a range oftools and approaches available that can span multiplelayers of the development stack. Today, developerspossess a wide variety of tools and frameworks thatcan be used to "mix and match" technologies.However, deploying multiple technologies createsseveral operational challenges, especially whenaddressing data governance and machine learningmodels, such as ensuring model performance parity inboth development and production environments. Inthis session, we will review these challenges, andthrough use cases see how developers andorganizations are overcoming them.

Participants

Thomas Dyar - Product Specialist, Intersystems

Make Education Great Again


We will share how we transform education fieldthrough specific AI technology with our researchprogress in this field. Also we will share our thoughtson how this AI application in education makes realimpact on education industry as well as on the wholesociety and community we're living in.

Participants

Youngduck Choi - AI Tech Leader, Riiid



Party at the DiSCO - How to Start Your OwnData Science Center of Excellence


Organizational leaders are being bombarded with AIand all the hype that goes with it. Many are throwingtheir hands up out of frustration while others arechasing the wrong projects, wasting time, money andopportunity. The best solution for most organizationsis to find someone on the inside with the knowledgeand network and arm them with a data science centerof excellence. In this session, we will share the journeywe've undertaken at Mount Sinai to create our ownData Science Center of Excellence (aka the DiSCOparty), what types of services can we offer, even on ashoe string budget and how we can quickly delivervalue to the business where they need it most - bypreparing the culture for change.

Participants

Mike Berger - VP, Chief Data & Analytics Officer, MountSinai Health System





The Power of Conversational AI and How it CanTransform CX


Consumers hate using ineffective technology tocommunicate with brands, whether it be dated IVRs ornewer but limiting chatbots. Wait times, limitedoptions, robotic systems, lack of personalization andhaving to repeat themselves are just a few of the manyreasons why ineffective systems infuriate consumers.While AI-powered solutions claim to solve all theseproblems and transform the customer experience(CX), implementing AI requires a customer-firststrategy. Join Interactions to learn how conversationalAI coupled with human understanding is beingleveraged by leading global brands to transform CXand increase customer engagement, while alsoproviding significant and demonstrable operationalsavings.

Participants

Priyanka Tiwari - Director of Product Marketing,Interactions





Introducing AI to The Contact Centre / ServiceCentre - OPEX Reduction Masterclass forSenior Strategists






How Machine Learning Puts the NBA Fan at theCenter


The NBA is the premiere global basketball league. In aworld where fewer than 1% of fans will experience anNBA game in person, the NBA provides its primaryinternational digital offering – the NBA League Pass –to fans to watch basketball. In the past year, the NBAhas begun internally developing machine learningtools to inspire, discover, and engage fans around theworld. In this talk, we address the trade-offs betweensupervised and unsupervised learning methods tobetter connect with fans, the importance of feedbackloops in machine learning, and how we’re using keyprinciples of data science to drive a data first culture.Our results demonstrate that putting the fanexperience at the center of our machine learningefforts drives fan engagements.

Participants

Erik Nylen - Senior Director, Data Science Lead, NBA

Can New Approaches to GPU MachineManagement Speed Delivery of Deep LearningProjects?


In many organizations that have taken on deeplearning (DL) initiatives, GPU resources are allocatedstatically or even managed manually insidespreadsheets. Companies buy expensive GPU serversbut don’t have control, visibility, or a way to maximizeutilization of GPUs efficiently for their users. This leadsto training bottlenecks and resource allocation issues,impacting the productivity of data scientists, the timeto production for DL projects, and the rapid escalationof infrastructure costs.

In this session, led by Omri Geller of Run:AI, we willexamine new approaches to the problem of GPUmachine management that can maximize resourceutilization for deep learning:

· What’s been done in the past?

· Could Kubernetes alone, which is growing quickly inadoption, solve the infrastructure managementproblem?

· Could advanced scheduling concepts be applicable?

· What can we learn or adapt from HPC for DLprojects?

· Can virtualization concepts be applied to better utilizeGPUs?

Participants

Omri Geller - Co-Founder and CTO, Run:AI

Figuring out Applied ML: Building Frameworksand Teams to Operationalize ML at Scale


Solving the hard problems requires operationalizingML at scale. Doing that in a definable and repeatableway takes planning and practice. Understanding howto match the deep understanding of subject matterexperts to the technical application of ML programsremains a real barrier to applied ML in the workplace.

Participants

Nels Lindahl - Director, Clinical Decision Systems, CVSHealth

AI & The Magic Customer-Getting Machine


Participants

Will Thompson - VP and Managing Director, ThoughtLeadership, Forbes





Workshop: Exploring ComputationalApproaches for Cancer Research


New computational opportunities and challenges haveemerged within the cancer research and clinicalapplication areas as the size, number, variety, andcomplexity of cancer datasets have grown in recentyears. Simultaneously, advances in computationalcapabilities, with exceptional growth in deep learning,are expected to continue to reach unprecedentedscales. Such opportunities to impact cancercomputationally are underscored in the 2016 USTwenty-first Century Cures Act and internationalefforts such as the ITCC-P4 focusing on developmenttreatments for pediatric cancer.

The workshop focuses on bringing together interestedindividuals ranging from clinicians, mathematicians,data scientists, computational scientists, engineers,developers, leaders and others with an interest inadvancing the use of computation at all levels to betterunderstand, diagnose, treat and prevent cancer. As aninterdisciplinary workshop, the cross-disciplinarysharing of insight and challenges fosterscollaborations and future innovations to accelerate theprogress in computationally and data driven cancerresearch and clinical applications.

A special emphasis for the 2019 workshop is the roleof computing in drug discovery for cancer, with aspecial emphasis on the role of AI, machine learning,and deep learning approaches applied to drugdiscovery and precision medicine.

Participants

Eric Stahlberg - Director of Biomedical Informatics andData Science (BIDS), Frederick National Laboratory forCancer Research

Frank Alexander - Deputy Director of theComputational Science Initiative, U.S. Department ofEnergy’s (DOE) Brookhaven National Laboratory

Panel: Operationalizing ML Across TheBusiness - How to Best Join Up Data Strategyand Model Deployment with ExistingOrganisational Structures


Participants

Rob DiCesare - CEO and Co-Founder, Galahad Group

Aditi Baker - Vice President - Head of Pricing &Portfolio Analytics, Primary Casualty, AIG

Rajeev Sambyal - Director of Artificial Intelligence &Innovation, BNY Mellon

Adi Ghosh - Senior Director - Lead, Financial ServicesInnovation Labs, Publicis Sapient

Sushil Thomas - VP Engineering, Machine Learning,Cloudera

Niranjan Thomas - General Manager, DeveloperPlatform & Solution Engineering, Dow Jones

Intelligent Experimentation Using BinomialMulti-Arm Bandit


At PayPal, Experimentation is the standard to measurethe impact of products we are building. From front-endUI changes to backend changes, the data-drivendecisions to pick a winning variant is facilitated by ourexperimentation platform. In this talk, we share howwe leveraged Machine Learning to invigorate ourplatform with the intelligence to dynamically adapt tochanging product requirements and optimize

Participants

Nisha Bhaskaran - Machine Learning Engineer, PayPal

Unleashing Your Organization's HumanIntelligence with AI


When 80% of an organization’s human intelligencegoes undocumented, it requires innovative thought-leaders to uncover the right technology to lead aworkforce revolution to solve. Starmind’s self-learningalgorithms will create neural know-how networkscapturing your organizational intelligence. Key benefitsinclude:

* Easily identify experts across your entire employeebase

* Create real-time AI skill profiles for talentmanagement, recruiting and workforce planning

* Single-point anytime access to your organizationalnetwork from anywhere, on any device

Participants

Eric Storm - Vice President, Americas, Starmind

Consumer Segmentation for Marketing andProduct Strategies Using Various MachineLearning Techniques


• It’s important for Companies to develop ConsumerSegmentation that groups consumers withcommon characteristics lumped together toestablish strategies for marketing, product &services and base management. Each marketsegment is unique, and can incorporate variouscriteria to create a target market for their productor service. Each segment can be approacheddifferently, after fully understanding the needs,attitudes, lifestyles, demographics, and personalityof the target consumer.

• Several machine learning algorithms have beentested leveraging survey attitudinal, internalbehavioral and demographic data to develop aconsolidated market segmentation.

• Machine learning algorithms including k-means,hierarchical clustering and Kamila clustering weretested with varying number of clusters to establishmarket segments.

• Final statistically significant segmentation modelgrouped consumers into unique clusters thatdifferentiated consumers in attitudes, life timevalue, behavioral and demographics establishing afoundation for unified strategy across the board.

Participants

Ranjit Jangam - Executive Director, Data Science,Comcast





Answering Hard Questions: Practical Examplesof Analyzing Text to Solve Real Problems inPharma


Participants

Ryan Welsh - Founder & CEO, Kyndi

The Art and Science of Hyper-Personalized CXWith Security at its Core


Today’s consumers want and expect a deeplypersonalized experience, and brands who can deliver itwill win. The AI technology to push hyperpersonalization is not the issue – that’s available andimproving at rapid speeds. What enterprises aregrappling with is how to deploy that technology in asecure way while striking a balancing act – the rightlevel of personalization into preferences and behaviorswithout crossing the line into invasive. With access tocustomer data across many points in an enterprise,brands must go beyond local regulations to protect itor they risk losing trust – the gold for any customerexperience program. In this session, Seb Reeve willleverage his experience working with Fortune 1000brands to explore how to deploy AI in an ecosystemthat delivers a personalized user experience whileensuring consumer security and fraud preventionalong the way, using data in a manner that respectscustomer privacy, complies with industry standards,and creates brand loyalty and trust.

Participants

Seb Reeve - Director of International Go-To-Market,Intelligent Engagement, Nuance Communications

Responsible AI – Ethical Data Leadership for aSustainable Future


Increasingly, more enterprises are exploring the use ofmachine learning and artificial intelligence (AI) in thedevelopment of their products, services and solutions.AI’s increasing profile holds great potential forincreased efficiencies, innovation and growth—both incommercial and “for-good” spaces. This promise canonly be fully realized if AI applications are carried outin a way that is responsible, ethical and honorsindividuals.

Chief Data Officer, JoAnn Stonier, will discussMastercard’s approach to responsible AI use andbroader commitment to responsible and human-centric data innovation and product design.

Participants

JoAnn Stonier - Chief Data Officer, Mastercard

Quantum Inspired Computing - Real examplesof visionary companies taking Data Scienceand AI to higher levels of performance today


Participants

Thierry Kahane - AI and Analytics Practice Leader forNorth America, Fujitsu

ABEJA Platform: Orchestration of HumanIntelligence and Artificial Intelligence withQuality Assurance


Founded in 2012, ABEJA group, a leading companyspecialized in Deep Learning in Asia, has a wealth ofexperiences in AI implementation with over 200companies, especially in Retail, Manufacture,Logistics, Finance, and Healthcare, and provides end-to-end solution for enabling AI process through theABEJA Platform. Powered by annotation tool and highperformance ML/DL algorithms, ABEJA providesABEJA Platform and ABEJA Insight for Retail to deliverstate-of-the-art solutions on cloud infrastructure for awide range of industries. Supported by Capital andBusiness Alliance with Google, NVIDIA, andSalesforce.com, ABEJA has just started business inthe U.S. to realize our vision, “Implement a FruitfulWorld”.

Participants

Yousuke Okada - Founder & Chief Executive Officer,ABEJA Technologies, Inc.

Becoming Information Driven: The Impact ofIntelligent Search for Big Pharma


Pharmaceutical companies need a new engine fordrug development to meet higher patient expectations,more stringent regulatory demands, and extremepressure from global competition. Trends such as thedigitization of healthcare data along with advances incomputing power and AI create opportunities totransform operations and harness the forces ofchanges.

Organizations know they should do something, but notall problem solving approaches are equal. Some holdpromise while others present only peril. This sessionwill help navigate the complex problem and solutionlandscapes while covering the following topics:

• Industry drivers and technological trends• Transformation imperatives• Technology tools that minimize complexity &

accelerate timelines• Example use cases and recommendations

Participants

Scott Parker - Director of Product Marketing, Sinequa

Right Messages, Right Time, Right Channels -Targeting HCPs with AI and ML


Participants

Hemal Somaiya - Global Marketing Director, MerckGroup

Embedding your AI and ML teams in yourbusiness: A Google approach


Participants

Rich Dutton - Head of Machine Learning for CorporateEngineering, Google

Scaling POC Success - Delivering Proven AIProduct Implementation Across Different Linesof Business - A Framework


Participants

Farah Gasmi - Director of AI Products, Argo Group





AI for Faster and Better Decision Making inMonitoring Oil and Gas Assets


In the oil and gas industry, continuous well surveillanceand monitoring is a vital part of upstream operations.Maintenance for thousands of wells in a given fieldcan result in a significant amount of man hourstraveling to sites, diagnosing, and resolvingmechanical issues.

Furthermore, when problems arise with a producingwell, it often results in intervention and shutting a wellin, which can impact production for an unforeseenamount of time.

As a solution, machine learning techniques areleveraged to monitor the overall health of a producingwell in order more efficiently route field technicians towells indicating early distress signals, thus mitigatingpotential downtime.

Participants

Trace Smith - Lead Data Scientist, ExxonMobil

How to Tag Medical Records to Create VitalData & Analytics


Learn about annotating medical records and howusing AI/ML with subject matter expertise is important– how to do this, why it matters, and how to use thedata for AI systems.

Participants

Doug Kemp - SVP and Managing Partner, Synodex LLC,Innodata

Boosting Social Media Success With AI-Powered Post Recommendations


Participants

John Shehata - Vice President, Audience DevelopmentStrategy, Conde Nast







Networking Lunch


Networking Lunch


Selecting Solvable Problems: A Hackers Guideto Augmenting Workflows with AI


One of the most common problems in the AI/MLdevelopment space is centered around teams takingon problems that, after weeks or months of work, turnout to be intractably hard to model or which requireextensive R&D to go from a toy example to somethingpractical and production quality. This talk is focusedon how to identify problems which are well suited toAI/ML solutions, and how to “start small and think big”,by iteratively moving from minor workflowaugmentations to full fledged automation.

Participants

Kevin Harris - Offensive Security Engineering Lead,Viasat

AI Product Manager & Chief Product OfficerHosted Roundtables - Building an AI ProductTeam That Delivers


Announcing The AI Summit NY Innovator of theYear Award


The Role of AI in Structure Based Drug Design,Advantages and Challenges


This session will cover:

• The steps involved in early stage (preclinical) drugdevelopment and the different sources andstructure of data involved in each stage

• The advantages of AI applications in each step andthe challenges encountered, with a particularaccent on the problems pertaining to data qualityand structure

• The advantages of applying AI to enhance therational aspects of drug design and theinvolvement of structural information

Participants

Rafael Depetris - Principal Scientist, Kadmon

AI as Creative Collaborator


Professionals in creative fields already use softwareplatforms with automated features that rely on AI forwriting, film editing, animation and design. New AIcapabilities and platforms increase the potential forautomated generation of creative content acrossdisciplines. This talk will focus on the opportunity fordevelopers of automated systems to bring humancollaborators into the loop, and the role humancreatives can play when empowered to influence theapplication of algorithms.

Participants

Claire Mitchell - Director, Innovation, VaynerMedia

Scaling POCs Across Different BusinessDivision / Units - Masterclass Session forSenior Practitioners


AI to ROI: Leveraging data to maximise yourreturns


Participants

Josh Sutton - CEO, Agorai





Automation Lessons from the Trenches


Knowledge workers in banking typically a) accessdata, b) analyze it and then c) reach a conclusion.Automating these series of tasks, mechanizesrepetitive/manual tasks. This frees up people to focuson the more value added activities. Salah will share aseries of lessons from banking trenches on how to dothis using a use case within Risk Management.

Participants

Salahuddin Khawaja - Managing Director, Automation/Global Risk, Bank of America

AI & Cybersecurity: Teaming up to DefendAgainst Current and Future Cyber Threats


On paper, it looks like we are fighting a losing battle.There are more threats facing our organizations andmore unfilled cybersecurity roles than ever before. Tocombat this reality, we must use all resources withinour grasp. This talk features prominent figures incybersecurity and founders of the Hacker Valley Studiopodcast Chris Cochran and Ronald Eddings. This talkwill explore how AI is helping the fight today and whatit might look like in the future.

Participants

Chris Cochran - Threat Intelligence and OperationsLead, Hacker Valley Studio

Ronald Eddings - Security Architect Leader, HackerValley Studio

Creating Ground Truth at Scale in DomainsRequiring High Subject Matter Expertise


Dr. Sina Bari, Director of Medical AI at iMerit, will focuson the following:

• Overcoming obstacles to create ground truth datafor ML applications

• Labeling best practices in fields that require highsubject matter expertise using case studies

• Framework for maximizing quality and minimizingcost across use cases

Participants

Sina Bari - Director of Medical AI, iMerit

Rebel Bot Bootcamp: Put Your Fat & ConfusedBots on the Pragmatic Diet


A team of engineers worked tirelessly to buildchatbots that could talk to us like a good friend. Butthis has lead to an empire of fat chatbots that couldn’tdeliver on their promises. Brands and customers alikewere left disappointed and frustrated. But now, a bandof rebels is applying AI pragmatically to deliver a newhope for the future of customer service, where theempire of fat chatbots is replaced by lean and agilechatbots that truly bring customer support into thedigital age. Join this session with Helpshift founderand CSO, Abinash Tripathy and learn a pragmaticapproach to AI and chatbots that delivers on itspromises.

Participants

Abinash Tripathy - Co-founder and Chief StrategyOfficer, Helpshift

Responsible AI - Practical Steps to EnsuringThe Delivery of Legal and Ethical AI


Ms. Pierce and General Huston will provide practicaltips to help you adopt Ethical AI. They will give realworld examples - including both successes andfailures - of implementing and scaling “AI for Good”across your organization. This will include a road mapfor leaders to develop legal, ethical, and responsiblepractices. They will also discuss the importantrelationship between industry and government to helpyou navigate contracts, laws, and emergingregulations.

Participants

General Patrick Huston - Assistant Judge AdvocateGeneral for Military Law and Operations (MLO), U.S.Army

Natalie A. Pierce - Shareholder, Co-Chair, Robotics, AIand Automation Practice Group, Littler

INNOVATION SHOWCASE


Drop by The Develop Stage for a host of 10 minute,quick-fire presentations from the hottest start-ups atthe absolute bleeding edge of the market.

Expect concise and commercial presentations fromstart-ups with ready-to-go solutions for some of themost pressing challenges enterprises face whenattempting to deliver AI across their business!

If you're looking for new, agile businesses with uniquesolutions, this is where you'll find them.

14:40 - Voice UX: A Platform-Based Approach to VoiceApplications - Andrei Papancea, CEO, NLX.ai

14:50 - How AI Can Solve The ‘Too Long Didn’t Read’Crisis: Why We Need a New Information Format, NosaOmoigui, Fonder and CEO, Weave

15:00 - AutoML: Simplified, Head of Sales andPartnerships, Gabriel Phillipe, Prevision

15:10 - Maintaining Reproducibility When DeployingMulti-Stage Data Pipelines, SeniorRepresentative, Pachyderm

15:20 - Deploying AI Decision Engines and DigitalAssistants to Leverage Data and Inspire Customers,Rob DiCesare, CEO and Co-Founder, Galahad Group

15:30 - Building Smarter Apps using AI - EnablingIntelligent Software Engineering, Sumanth Vakada,Founder & CEO, Qualetics

15:40 - Effective AI for medical devices - Case studiesin image segmentation, landmark detection andendoscopic video analysis, RSIP Vision, CEO, MoscheSafran

15:50 - Art as an Interface for Wearable Technology,Philip H Wilck and Tiia Vahula, Utopia Blu

Participants

Andrei Papancea - Co-Founder and CEO, NLX Inc.

Nosa Omoigui - Founder and CEO, Weave

Gabriel Philippe - Head of Sales and Partnerships,Prevision

Speaker(s) TBA - Senior Representative, Pachyderm

Philip H Wilck - Creative Director and Founder, UtopiaBlu

Tiia Vahula - Co-Owner, Utopia Blu

Rob DiCesare - CEO and Co-Founder, Galahad Group

Scaling AI across your large-scale enterprise:the real goal


Participants

Ravi Boggaram - CTO and Sr. Director - Global DigitalServices, PepsiCo





How Well Does AI Understand Culture?


Culture encompasses shared human experiencesranging from music and food to everything in between.Culture brings us closer together, shapes our style, andinforms our opinions. Until now, our interpretation ofculture has primarily been a by-product of human tohuman interaction. Let's consider for a moment howwell AI understands culture and what therepercussions are.

Participants

Lawrence Edmondson - Senior Vice President ofTechnology, VaynerMedia

AI and Machine Learning for ConsumerHealthcare at GSK


This session will cover 4 top use-cases at GSK:

• Seasonal Illness - Predictive Learning – Howinternal and external data sources are consideredfor Machine Learning-based predictive modelling,focusing on:

1. Predictive illness forecasting and the processfor informing consumers

2. Plan for media, supply chain, and collaborationwith retailers for activation

• Wellness - looking at how Machine Learning isused for image recognition and classification inoral hygiene products to inform consumers abouttheir condition and recommend dentist's help

• Mobile Eye tracking - How mobile tracking usingtracking glasses is used to analyze shoppers'behavior in our Shopper’s Science Lab, helping GSKcollaborate with retailers to place products incorrect shelf positions and plan promotions

• Cognitive Voice Chatbot Services - How GSK istraining chatbots with different voice samples sothe chatbots and voice search can recognizecomplex OTC products with different samples

Participants

Subroto Mukherjee - Head of Innovation and EmergingTechnology, Americas, GlaxoSmithKline

Making Money with Voice Commerce


We are now talking to our TVs, our cars, our smartspeakers and our mobile devices. It turns out we canspend money faster with our mouths than our fingers,and voice commerce is already a burgeoningopportunity for sellers who know how to cash in. AskSiri and Alexa about your products to find out whatthey know about you. If your company is like most,you may be disappointed to learn that Siri and Alexadon’t know you at all and your customers can’t buyyour products using voice. This session is for thoseeager to sell using voice commerce. Learn to speakup through the voice user interface or be prepared forsilence.

Participants

William Ammerman - EVP, Digital Media, EngagedMedia



Networking Break


Afternoon Networking Break


Fireside Chat: Augmenting CustomerExperience with ML in eCommerce


• How is the eCommerce industry being transformedoverall by new advancements in AI and ML?

• What are the advantages and disadvantages ofpersonalized vs. non-personalizedrecommendations?

• What are some of the challenges involved withharnessing data for customer recommendationson digital platforms?

• Build or buy – what are the primary considerationswhen deciding how to implement a productrecommendation engine?

Participants

Asma Farooq - Product Lead, Advertising, eBay

Structuring a Data Science team to focus onSales and Marketing


To drive revenue, most businesses seek to providevalue to their customers through targeted messagingat the right time and place. At the same time, today’s e-commerce landscape is changing at an unprecedentedpace. The rise of new international markets, newplatform and technologies, combined with constantlyevolving user habits and preferences, means thatbusinesses and Marketing units must constantlyevaluate and adapt their strategies to remaincompetitive. Data Science and Engineering can play akey role in this space, and provides significant benefitswhen looking to operate, market and connect withcustomers.

In this talk, we will describe how to best structure aData Science team focused on Sales and Marketing.We will discuss practical examples on how to drivereal business value through the application of bothsimple and complex methods, and highlight theimportance of applying traditional softwareengineering principles. Finally, we will discuss variousways of communicating back to the business, and theneed to balance insights, algorithms and dataengineering.

Participants

Thomas Vincent - Senior Director, Head of DataScience, Getty Images

Why the Privacy Company is the MostImportant Business You Have Never Heard Of


Tech ethicists commonly worry about privacy beinglost in a world of artificial intelligence, but what exactlyis privacy, and why does it make a tangible differencein our lives? With compelling examples, JamesBrusseau answers the questions in his talk titled, Whythe Privacy Company is the Most Important BusinessYou’ve Never Heard Of.

Participants

James Brusseau - Director - Data Ethics Site, PaceUniversity

Chairperson's Closing Remarks


Reserved for Industry Partner






Generating Business Value from your AIInvestments


In this session you will learn:

How to build a culture of experimentation and "fastfail"How to scale solutions to the enterprise levelHow to ensure adoption and ongoing usage inbusiness teams

Participants

Rahul Tyagi - Analytics Director, Former ColPal

Leveraging Machine Learning and AI toImprove Quality and Patient Safety: Lessonsfrom the Frontlines


This session will explore one organization's journeywith embedding AI into hospital operationsand clinicalworkflows. We will cover the framework used todevelop and deploy real-time products that predict:Clinical Deterioration, Malnutrition, and Falls. We willshare how these tools are being leveraged at scaleacross a multi-hospital system to enhance patientsafety, quality of care, and the patient experience.

Participants

Robbie Freeman - Vice President, Clinical Innovation,Mount Sinai

COMING APART: A conversation about themechanics of how we became one nationdivided by content, and what we can do about it


The Unites States is more politically divided now thanwe have been in the last twenty-five years, and it isdata that has been the essential element in creatingthe wedge.

Our most recent three Presidential election cyclestrace the rapid maturation of data’s application indigital message targeting and its increasingly effectiveuse in impacting election outcomes.

This panel explores the perfect storm of otherwiseinnocuous commercial technology capabilities thatcollided to create today’s psychographic messagingsuperweapons, the cultural effects on oursociopolitical discourse, and new thinking onapproaches to remedy before the unthinkablehappens.

Participants

Michelle Brattain - Associate Professor and Chair ofthe Department of History, Georgia State University

David Vanderpoel - Lead Experience Strategist, Slalom

James Brusseau - Director - Data Ethics Site, PaceUniversity

Thomas Stubbs - Vice President of Engineering andInnovation - Coca-Cola Freestyle, Coca-Cola Company

Callisto: Tactical Decision Intelligence inHealth Management


Managing the care trajectories of patients over time isthe single most impactful way to improve populationhealth, decrease wasteful healthcare utilization, andcontain runaway healthcare spending. Johns HopkinsHealthcare’s model, Callisto, predicts patients forwhom health management programs will deliver aconcrete return in the form of better overall health(lower disease burden) and lower unnecessaryutilization. The model is made up of 3 interlockingmodels that work together:

1. Future Utilization: this model predicts a patient’sfuture utilization patterns, allowing physicians tointervene in a patient’s care as their disease burdenis rising, rather than waiting until the disease hasprogressed.

2. Regression to the Mean: many patients will regressto the population average after a high cost, highutilization episode, all other things equal. Thismodel predicts patients who are likely to revert to alower cost state and those who are likely to stayhigh utilizers permanently.

3. Impactability: Not all patients are equallyimpactable by health management activities. Thismodel predicts patients who will be.

Participants

Romy Hussain - Director, Healthcare Economics,Johns Hopkins Healthcare

Closing remarks









6) AI HEALTHCARESUMMIT

7) AI SALES, MARKET-ING AND CX SUMMIT

LOUNGE 1: AI FORBESBOARDOOM - CXOSEMINARS



09:00 09:00 - Welcome Ad-dress

09:10 - Making DataScience Useful

09:35 - Microsoft AI:Powering new Possi-bilities for your Enter-prise

09:30 - Welcome fromChair

09:40 - NSCAI Dia-logue with Industry

09:25 - Chair's Open-ing Remarks

09:30 - Go Global orGo Home - How tobuild a profitable inter-national AI Business.

09:55 - AdvancedClustering Techniquesfor Audience Segmen-tation

09:20 - Chairperson'sWelcome and Intro

09:35 - HumanisticCare in the Age of AI

09:10 - Chairperson'sWelcome and Intro

09:35 - AI/ML Ad-vances and Impactson Sales and Market-ing

09:00 - AI BusinessModel ReinventionWorkshop

09:00 - Introduction toNatural Language Pro-cessing

10:00 10:00 - How is AI ex-tending the customerlife time value atBanorte

10:25 - Evolving froman insurer to a fintech:how will your busi-ness evolve?


10:00 - Where MLModels Meet The RealWorld

10:20 - PredictingContent Virality to Dri-ve Social Traffic

10:40 - Make Educa-tion Great Again

10:15 - A Data-Sharing Model To Ac-celerate the Imple-mentation of AI inPharma

10:35 - From data todeployment and back:Challenges across theapplication develop-ment journey

10:00 - How to Startand Scale AI-PoweredAutomation In LifeSciences

10:25 - Convergent AIin Medicine – ReduceWastes, Do No Harm,and Avoid Misdiagno-sis

10:50 - Party at theDiSCO - How to StartYour Own Data Sci-ence Center of Excel-lence

10:00 - PerformanceLinguistics: The En-gine Driving AI Suc-cess

10:25 - AI in Market-ing in the Age of Hu-mans with Machines

10:50 - The Power ofConversational AI andHow it Can TransformCX

10:30 - Intelligent RPAWorkshop - Platform +Use Case Discovery













11:00 11:55 - UnleashingYour Organization'sHuman Intelligencewith AI


11:30 - How MachineLearning Puts theNBA Fan at the Center

11:50 - Panel: Opera-tionalizing ML AcrossThe Business - How toBest Join Up DataStrategy and ModelDeployment with Ex-isting OrganisationalStructures


11:30 - Can New Ap-proaches to GPU Ma-chine ManagementSpeed Delivery ofDeep Learning Pro-jects?

11:50 - Intelligent Ex-perimentation UsingBinomial Multi-ArmBandit


11:45 - Figuring outApplied ML: BuildingFrameworks andTeams to Operational-ize ML at Scale


11:45 - AI & The Mag-ic Customer-GettingMachine

11:00 - Introducing AIto The Contact Centre/ Service Centre -OPEX Reduction Mas-terclass for SeniorStrategists

11:45 - Workshop: Ex-ploring ComputationalApproaches for Can-cer Research

12:00 12:20 - Responsible AI– Ethical Data Leader-ship for a SustainableFuture

12:45 - Embeddingyour AI and ML teamsin your business: AGoogle approach

12:30 - Quantum In-spired Computing -Real examples of vi-sionary companiestaking Data Scienceand AI to higher levelsof performance today

12:50 - Scaling POCSuccess - DeliveringProven AI Product Im-plementation AcrossDifferent Lines ofBusiness - A Frame-work

12:10 - ConsumerSegmentation forMarketing and Prod-uct Strategies UsingVarious MachineLearning Techniques

12:30 - ABEJA Plat-form: Orchestration ofHuman Intelligenceand Artificial Intelli-gence with Quality As-surance

12:50 - AI for Fasterand Better DecisionMaking in MonitoringOil and Gas Assets

12:10 - AnsweringHard Questions: Prac-tical Examples of Ana-lyzing Text to SolveReal Problems inPharma

12:35 - Becoming In-formation Driven: TheImpact of IntelligentSearch for Big Phar-ma

12:10 - The Art andScience of Hyper-Personalized CX WithSecurity at its Core

12:35 - Right Mes-sages, Right Time,Right Channels - Tar-geting HCPs with AIand ML













13:00 13:10 - Lunch breakand opportunity to vis-it the expo



13:00 - How to TagMedical Records toCreate Vital Data &Analytics


13:00 - Boosting So-cial Media SuccessWith AI-Powered PostRecommendations


14:00 14:10 - AnnouncingThe AI Summit NY In-novator of the YearAward

14:20 - AI to ROI:Leveraging data tomaximise your returns

14:45 - Scaling AIacross your large-scale enterprise: thereal goal

14:20 - AutomationLessons from theTrenches

14:40 - Responsible AI- Practical Steps toEnsuring The Deliveryof Legal and Ethical AI

14:00 - Selecting Solv-able Problems: AHackers Guide to Aug-menting Workflowswith AI

14:20 - AI & Cyberse-curity: Teaming up toDefend Against Cur-rent and Future CyberThreats

14:40 - INNOVATIONSHOWCASE

14:10 - The Role of AIin Structure BasedDrug Design, Advan-tages and Challenges

14:35 - CreatingGround Truth at Scalein Domains RequiringHigh Subject MatterExpertise

14:10 - AI as CreativeCollaborator

14:35 - Rebel BotBootcamp: Put YourFat & Confused Botson the Pragmatic Diet

14:00 - AI ProductManager & ChiefProduct Officer Host-ed Roundtables -Building an AI ProductTeam That Delivers

14:15 - Scaling POCsAcross Different Busi-ness Division / Units -Masterclass Sessionfor Senior Practition-ers

15:00 15:10 - Afternoon net-working break

15:40 - Structuring aData Science team tofocus on Sales andMarketing

15:00 - How WellDoes AI UnderstandCulture?

15:20 - NetworkingBreak

15:45 - Why the Priva-cy Company is theMost Important Busi-ness You Have NeverHeard Of

15:00 - AI and Ma-chine Learning forConsumer Healthcareat GSK

15:25 - Afternoon Net-working Break

15:00 - Making Moneywith Voice Commerce

15:25 - Fireside Chat:Augmenting Cus-tomer Experience withML in eCommerce

15:50 - Chairperson'sClosing Remarks













16:00 16:05 - Reserved forIndustry Partner

16:25 - COMINGAPART: A conversa-tion about the me-chanics of how we be-came one nation di-vided by content, andwhat we can do aboutit

16:05 - GeneratingBusiness Value fromyour AI Investments

16:05 - LeveragingMachine Learning andAI to Improve Qualityand Patient Safety:Lessons from theFrontlines

16:30 - Callisto: Tacti-cal Decision Intelli-gence in Health Man-agement

17:00 17:05 - Closing re-marks





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