the department of statistics - university of connecticut · i would like to welcome victor hugo...

The

Department

of

Statistics

Fall 2017

Newsletter

A Message from the Department Head 3

From the Director of the Graduate Program 6

From the Director of the Undergraduate Program 8

Selected Faculty Activities 9

From the Director of the Statistical Consulting Services 36

On His 125th Birth Anniversary, Reminiscence of Prasanta Chandra

Mahalanobis and His Impact on Today’s Statistical Science

39

An Update from the New England Statistical Society 42

New England Statistical Society Membership Form 46

Faculty News and Awards 48

Annual Department Picnic and Graduate Student Awards 49

Colloquia 51

The 2017 Conference on Lifetime Data Analysis at UConn a Success 54

QPRC 2017 57

Math Alliance 58

NESS 2017 58

IWAP 2018 63

Alumni News 64

Student News 70

Recent Graduates 72

Alumni Reply Form 73

Department Directory 73

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Welcome to the twentieth issue of our Department Newsletter. I

am very pleased to report that we have had a very busy but

productive year (2016-2017). During Fall 2016 and Spring 2017,

the department underwent the eight-year (2008-2016) program

review. The department hired two assistant professors, one full

professor, and one visiting assistant professor in Spring 2017. The

department also hosted three national/international conferences

consecutively in April, May, and June 2017. I would like to thank

all faculty members, staff, and students for their great effort and

hard work to complete so many tasks within the same year. The

department continues to grow and blossom in all aspects.

Currently, we have 20 tenured and tenure-track faculty members, two visiting assistant professors,

three lecturers, two adjunct faculty members, and eight joint faculty members from UCH,

Computer science & Engineering, Ecology and Evolutionary Biology, Allied Health Science,

Mathematics, and Nursing Instruction and Research, who have joint appointments with Statistics.

In Fall 2017, we also have 117 graduate students enrolled in our graduate program, of whom 46

have received financial support, 143 Statistics major or double major undergraduate students, 83

Math-Stat major undergraduate students including 1 Math-Stat double major, and 103 Stat minor

undergraduate students.

I would like to welcome Victor Hugo Lachos Davila to join the Department as a full Professor, who

was a full professor at the Campinas State University, Brazil and a Visiting Professor at UConn last

year, and Yuwen Gu and HaiYing Wang to join the Department as tenure-track Assistant

Professors. I am also pleased to share that Panpan Zhang will continue to be with us as a Visiting

Assistant Professor for another year, and Néhémy Lim has joined the Department as a Visiting

Assistant Professor. It is great to have Yong Shang of Henan University of Economics and Law to

visit us as a Visiting Research Professor and stay in Storrs until March 2018.

I would like to congratulate Professor Jun Yan on being elected to Fellow of the American Statistical

Association (ASA). Congratulations also go to our Alumna Rongwei (Rochelle) Fu (Ph.D. 2003) on

her election to Fellow of ASA. I would like to congratulate our colleagues, Professors Kun Chen,

Zhiyi Chi, and Dipak K. Dey on recently receiving research grants from the National Institutes of

Health, the National Science Foundation, and Travelers.

A Message from the

Department Head

4

Ph.D. student Jing Wu was selected to receive one of the International Biometric Society Eastern

North American Region’s (ENAR) Distinguished Student Paper Awards for the 2017 ENAR Spring

Meeting (March 2017). Jing Wu also received the poster award at the 2017 Conference on Lifetime

Data Analysis in May 2017. Ph.D. student Gregory Vaughan won the Student Paper Award

Competition by the Mental Health Section of the ASA and presented his paper at 2017 JSM in

Baltimore. Ph.D. students Wenjie Wang and Yeongjin Gwon each received the IBM Best Paper

Award at the 31st New England Statistics Symposium held in April 2017. Ph.D. student Yang Liu

won an ACTNext Travel Award to attend the 2017 International Meeting of the Psychometric

Society in Zurich, Switzerland. Our undergraduate students, Francisco Tomas Cifuentes Villarroel,

Sarah Cynthia Crothers, Jessica Hope Lerner, Samuel Schick, and Emily Elizabeth Stiles were

elected to Phi Beta Kappa in March 2017. Congratulations to these students for their hard work

and research and academic excellence!

The department eight-year (2008-2016) program review went really well. I would like share with

you some highlights from our self-study report. During the period of 2008-2016, the department

faculty members published 580 peer-reviewed articles in leading journals, 61 book chapters, and

28 proceeding articles. They edited 19 books or proceedings and produced 6 patents. Active

extramural awards (2008-16) totaled $4,122,198 with our faculty as PI and $8,963,083 with our

faculty as Co-PI. Active intramural awards totaled $550,414 with our faculty as PI or Co-PI. During

this review period, our 17 regular faculty members, with 5 hired after 2012, delivered 233 invited

talks in major national and international conferences, 222 colloquium talks, and 62

workshops/short courses. The department has been actively engaging in research collaborations

and educational exchanges within the University, as well as across the world. Within the

University, the department maintains strong ties with many other departments and units.

Statistical Consulting Services (SCS) provides research support on an extensive scale to graduate

students and faculty within the University. Internationally, the department signed four

memoranda of agreements with universities in China and Brazil. The department has been

welcoming a steady stream of visitors and students from universities around the world. I am very

proud of our department accomplishments during the last eight years. Thanks to our faculty

members, staff, and students for their contributions and great effort. I would also like to thank

Professor Rick Vitale for chairing the Program Review committee and playing a critical role in

writing such a very informative and comprehensive self-study report.

It was the first time in the department history that three national/international conferences were

hosted by the department. The 31st New England Statistics Symposium (NESS) was held on April

21 and 22 and about 250 participants were in attendance. I would like to thank Professors Haim

Bar, Kun Chen, Jun Yan (Chair) and Yuping Zhang for organizing this symposium. I would like to

acknowledge Haim for taking over the chair role during Jun’s medical leave. The 2017 Conference

on Lifetime Data Analysis was held at Storrs on May 25-27, 2017. Jun Yan and myself co-chaired

the local organizing committee. This conference was sponsored by ASA LIDA-IG. The conference

was a great success. There were approximately 340 registrants and 63 sessions organized with

many excellent presentations over the course of the conference. QPRC 2017: the 34th Quality and

Productivity Research Conference was held on the Storrs campus during June 13-15, 2017. About

200 participants attended this three day conference. Thanks to Professors Nalini Ravishanker and

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Haim Bar for their exceptional organizing work towards making the conference a huge success.

These symposium and conferences help improve the visibility of the department, as well as the

University, since many participants visited the Storrs campus for the first time and they were

impressed by how beautiful the campus was.

UConn Statistics Department Alumni and Friends Dinner was successfully held in Tokyo Seafood

Buffet restaurant in Windsor Mill, MD on Monday, July 31, 2017, during the 2017 JSM. Over 20

guests attended the dinner. Several former students had not seen each other for many years after

they graduated from UConn. I would like to thank our alumna, Lan Huang (PhD 2004) of FDA, for

organizing this event. I would also like to thank our staff, Tracy Burke, and Andrew Kim of Alumni

Relations, College of Liberal Arts and Sciences, for their help and support. Without them, it would

be impossible for us to have such a successful event. I expect that we will host another Department

Alumni and Friends Dinner during the 2018 JSM in Vancouver.

The UConn Health Center has continued to support our students both from joint research grants

as well as from internship programs. We thank Professor Robert Aseltine, Interim Chair, Division

of Behavioral Science and Community Health and Deputy Director, Center for Public Health and

Health Policy, for his continuous sponsor of research collaborations with our faculty and graduate

students. We also thank Professor James Grady, Director of Biostatistics, Connecticut Institute for

Clinical and Translational Science, for providing financial support and research opportunities for

our graduate students. We are also enjoying close research collaboration with the Institute for

Collaboration on Health, Intervention, and Policy (InCHIP). Our Statistical Consulting Services (SCS)

is continuing with great success. Currently, SCS provides three types of full-consulting: project

service, walk-in services, and online services. SCS hosted two workshops in Fall 2016 and three

workshops in Spring 2017. In addition, the second SCS workshop day was held on Wednesday,

May 10, 2017. I would like to thank Professor James Grady for participating in the SCS workshop

day as a guest presenter for one of the three workshops. I would also like to thank our graduate

students who worked at the SCS for their great effort and hard work. We are grateful for the

financial support we have received for our SCS from the Office of Vice President for Research, and

the Dean’s Offices of the College of Liberal Arts and Sciences and the College of Agriculture, Health

and Natural Resources. The Pfizer Global Research & Development Student Fellowship Program

has been extended through Summer 2018. Our collaboration with the School of Nursing will also

continue through Spring 2018. I would like to thank Pfizer and the School of Nursing for their

continuous support of our graduate students.

Finally, I would like to share with you an exciting development. This year marks the 31st

anniversary of the New England Statistics symposium. Ever since its launch at UConn in 1987 at

the suggestion of Herman Chernoff, the symposium has been an intimate annual gathering of our

large statistical family in the region. Through its course, it has greatly fostered the growth and unity

of our community. To sustain such a success and build upon the lasting legacy of the symposium,

the department initiated the founding of a new statistical society called the New England Statistical

Society. The first interest group meeting was held on January 28, 2017 and 19 representatives from

13 universities or companies in New England and New Jersey participated in this historic event.

Three task groups including Journal, Strategies and Development, and Education were formed. This

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new society was incorporated as a non-profit organization on March 2, 2017 and received IRS Tax-

exempt 501 (c) (3) status on March 28, 2017. The society website, www.nestat.org, was online on

April 15, 2017. The new society was officially announced by the founding president, Xiao-Li Meng,

of Harvard University in the afternoon of April 22, 2017 during the 31th New England Statistics

Symposium at Storrs, CT. The office of this new society is located on the third floor of the Philip E.

Austin building on UConn Storrs campus. I cordially invite all of our alumni to become permanent,

lifetime members of the New England Statistical Society. You all are welcome back to Storrs to

have a visit to the department and to meet our new faculty members and students. Thank you all

for your continuous support!

Ming-Hui Chen ([email protected])

Our department has three graduate programs: Ph.D. in Statistics,

M.S. in Statistics, and Professional M.S. in Biostatistics. These

programs provide excellent learning and research experiences to

prepare students for a successful career in statistics. We offer a

broad spectrum of modern courses in statistics and probability,

covering advanced theories and methodologies, statistical

computing, data management, consulting, and practical skills that

are sought after in industry or health related fields. In advanced

seminar courses, students are exposed to exciting areas of current research. Through our

Statistical Consulting Services, students are engaged in research in many areas of science and

technology, and provide support to the research community of the University of Connecticut. We

have an extensive collaboration with faculty members in educational, medical, biological, health

and environmental sciences, and our graduate students have the opportunity to be employed as

research assistants on many of their funded research projects.

I am glad to announce that the first year of our new Professional M.S. program in Biostatistics was

a great success. We have 37 students currently enrolled in the program. Established in Fall 2014,

From the Director of

the Graduate Program

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the Professional M.S. program in Biostatistics focuses on practical skills that are sought after in

health related fields. Like our M.S. program in Statistics and Ph.D. program, this program provides

exciting opportunities to students.

During the past academic year, 47 new students were enrolled in our graduate programs, 9 of

them with support in the form of teaching or research assistantship from the department or a

variety of other sources. A total of 138 graduate students were enrolled, out of which 46 were

supported. We gratefully acknowledge the financial support from the Dean's Office of the College

of Liberal Arts and Science (CLAS), Dean's Office of the College of Agriculture, Health and Natural

Resources (CAHNR), Office of the Vice President for Research, and Pfizer, Inc.

Our graduate programs are highly competitive and visible around the world. This year over 561

students all over the world applied for admission to the programs. I would like to thank the

members of the graduate admission committee, Professors Harel (Director of Graduate

Admissions), Chen, Kuo, Ravishanker, Vitale, and Yan, for their hard work in reviewing the

applications. Thanks are also due to our administrative staff, Megan Petsa and Tracy Burke, for

their hard work throughout the application and admission processes. This Fall 2017 semester, we

welcomed 47 new students, 17 in the M.S. program in Statistics, 12 in the Professional M.S.

program in Biostatistics, and 18 in the Ph.D. program, with 9 of the new Ph.D. students supported

by the department.

An updated graduate brochure, providing information about the department, our graduate

programs and application forms along with instructions, is available on the department website:

www.stat.uconn.edu.

Zhiyi Chi ([email protected])

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Let me start by congratulating all of our recent graduates for

obtaining their Bachelor’s degrees and wishing them success in all of

their future endeavors!

The Undergraduate Program continues to grow and flourish. As of

Fall 2017, there are nearly 225 majors in Statistics and Mathematics-

Statistics. Of these, 15 are double majors. There are also over 100

students who plan to minor in Statistics. An individualized major in

Data Science has just been approved. We expect this to soon become a popular major.

All our course offerings remain in high demand with near-full enrollment. In Spring 2018, we will

offer a course on Data Science (STAT 4185) and a course on GLM (STAT 4188). Our summer session

offerings (STAT 2215 and STAT 3025) also continue to attract many undergraduate students. Our

graduates continue to achieve success in their academic careers, many being accepted to some of

the country’s leading graduate programs for statistics. We also continue to connect students with

undergraduate research opportunities, internships, and other resources. Our participation in the

UConn Early College Experience (ECE) Program, which allows interaction between UConn and high

schools across the state, also continues. By creating even more resources for potential and current

statistics majors, we have kept very busy, and we expect to achieve continued growth for the

program in the coming years.

Please visit the department website at www.stat.uconn.edu for the undergraduate brochure,

information about our undergraduate program, and information for prospective majors and

minors.

Let me conclude by thanking Elizabeth Schifano, Faculty Academic Advisor, for sharing the

undergraduate advising this past year and Lynn Kuo for holding the fort during my sabbatical leave

in Spring 2017. Alyssa O’Keefe from the CLAS Academic Services Center started advising freshmen

and sophomores starting Fall 2017. I also thank all the faculty who have been active in mentoring

our majors for UG Research through STAT 4389; the students have truly appreciated this.

Nalini Ravishanker ([email protected])

From the Director of

the Undergraduate

Program

9

Haim Bar gave the talk, “A Scalable Empirical Bayes Approach to Variable Selection in Generalized Linear

Models” at the 24th Quality and Productivity Research Conference, Storrs, CT June 2017 � the 10th ICSA

International Conference, Shanghai, China, December 2016 � Temple University, Research Colloquium,

Department of Statistical Science, April 2017 � Baruch College, CUNY, Colloquium, Department of

Information Systems and Statistics Zicklin School of Business, November 2016.

PI, NSF Award #1612625. Variable Selection in the High Dimensional, Low Sample Size Setting Beyond the

Linear Regression and Normal Errors Model � Co-PI, Travelers. Modeling and analysis of large insurance

claim and occurrence data: A partnership between UConn and Travelers.

Haim Bar is a co-chair of the organizing committee of the 31st New England Statistics Symposium, Storrs,

CT, April 2017 � Co-chair of the organizing committee of the 24th Quality and Productivity Research

Conference, Storrs, CT, June 2017.

Bar, H. Y. & Mentch, L. (2017). R-CMap - An open-source software for concept mapping. Evaluation and

Program Planning - Special Issue on: Concept Mapping at 25: Development, Applications, and

Future Directions, 60, 284-292.

Chen, K., Mishra, N., Smyth, J., Bar, H., Schifano, E., Kuo, L., & Chen, M.-H. (2017). A tailored multivariate

Haim Bar Assistant Professor

Selected Invited Talks

Outreach

Selected Publications

Photo with 1.5pt black

outline

Grants

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mixture model for detecting proteins of concordant change in the pathogenesis of Necrotic

Enteritis. Journal of the American Statistical Association.

Rom, O., Korach Rechtman, H., Hayek, T., Danin-Poleg, Y., Bar, H., Kashi, Y., & Aviram, M. (2017). Acrolein

increases macrophage atherogenicity in association with gut microbiota remodeling in

atherosclerotic mice: protective role for the polyphenol-rich pomegranate juice. Archives of

Toxicology, 91(4), 1709-1725.

Molinari, E., Bar, H., Pyle, A. M., & Patrizio, P. (2016). Transcriptome analysis of human cumulus cells

reveals hypoxia as the main determinant of follicular senescence. Molecular Human

Reproduction, 22(8), 866-876.

Associate Editor of Sankhya, the Indian Journal of Statistics, January 2016 - Present

Kun Chen was invited to give invited talks at the Department of Mathematics & Statistics, University of

Massachusetts, Amherst, MA in October 2016 � AMIA 2016 Annual Symposium, Chicago, IL in November

2016 � The 31st New England Statistics Symposium, Storrs, CT in April 2017 � IMS/ASA Spring Research

Conference, Rutgers University, New Brunswick, NJ in May 2017 � Modern Modeling Methods Conference,

Storrs, CT in May 2017 � 2017 ICSA Applied Statistical Symposium, Chicago, IL in June 2017.

Principal Investigator: Collaborative Research: Comprehensive heterogeneous response regression from

complex data. National Science Foundation (1718798). 09/01/2017– 08/31/2020 � PI on a subaward:

Improving the identification of patients at risk of suicide. National Institutes of Health (R01-MH112148).

07/01/2017–06/30/2020 � Co-PI (with Elizabeth Schifano and Jun Yan): Data Science Lab: Real-world data

Kun Chen Assistant Professor

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science problems meet future data scientists. UConn CLAS Fund for Innovative Education in Science.

01/01/2017–12/31/2018 � PI: Integrative multivariate analysis with multi-view data. National Science

Foundation (DMS- 1613295). 09/01/2016–08/31/2019 � PI on a subaward: An integrative statistics-guided

image-based multi-scale lung model. U.S. National Institutes of Health (U01-HL114494). 08/01/2013–

05/31/2018 � Co-PI (with Haim Bar, Elizabeth Schifano, Xiaojing Wang, and Dipak Dey): Modeling and

analysis of large insurance claim and occurrence data: a partnership between UConn & Travelers. Travelers

Insurance. 08/01/2017–07/31/2018 � Co-PI (with Elizabeth Schifano, Xiaojing Wang, and Dipak Dey):

Modeling and analysis of large insurance claim and occurrence data: a partnership between UConn &

Travelers. Travelers Insurance. 08/01/2016–07/31/2017.

Chen, K., Mishra, N., Smyth, J., Bar, H., Schifano, E., Kuo, L., Chen, M.-H. (2017). A tailored multivariate

mixture model for detecting proteins of concordant change in the pathogenesis of Necrotic

Enteritis. Journal of the American Statistical Association. In press. doi:

10.1080/01621459.2017.1356314

Chen, K. & Aseltine, R. (2017). Using hospitalization and mortality data to target suicide prevention

activities. Journal of Adolescent Health, 61, 192-197.

Mishra, A., Dey, D., Chen, K. (2017). Sequential co-sparse factor regression. Journal of Computational &

Graphical Statistics. In press. doi: 10.108/0/10618600.2017.1340891

She, Y. & Chen, K. (2017). Robust reduced-rank regression. Biometrika, 104(3), 633-647.

Editor of Bayesian Analysis � Editor of Statistics and Its Interface � Associate Editor of Journal of the

American Statistical Association � Associate Editor of Lifetime Data Analysis � Associate Editor of Journal of

Computational and Graphical Statistics


Ming-Hui Chen Department Head

Editorial Boards


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Ming-Hui Chen delivered keynote talks on “A Bayesian Cure Rate Frailty Model for Survival Data in the

Presence of Semi-Competing and Competing Risk” in the 2016 Big Data and Statistics Forum, Center for

Statistical Sciences and Mathematical College, Sichuan University, Chengdu, China, December 2016; and

“Bayesian Model Assessment in Joint Modeling of Longitudinal and Survival Data with Applications to

Cancer Clinical Trials” in Brazilian School of Regression Models XV, Goiania, State of Goias, Brazil, March

2017. He presented an Invited Tutorial Lecture on “Bayesian Computation: From Posterior Densities to

Bayes Factors, Marginal Likelihoods, and Posterior Model Probabilities”, at the 2nd ISBA-EAC Conference,

Northeast Normal University, Changchun, China, July 2017. He also gave a short course (4 full days) on

“Bayesian Statistics”, at the Statistics Graduate Summer School, School of Mathematics and Statistics,

Yunnan University, Kunming, China, July 2017. He gave invited talks on “Bayesian Modeling and Inference

for Nonignorably Missing Longitudinal Response Data with Applications to HIV Prevention Trials” in an

Invited Session on “Modern Bayesian Methods in Big Data and Precision Medicine” at the 10th ICSA

International Conference, Shanghai Jiao Tong University, Shanghai, China, December 2016; “Recent

Development on CPO Statistics in Joint Modeling of Longitudinal and Survival Data”, in Invited Session 19

on “Emerging Statistical Inference Methods in the Era of Data Science” at the 2017 Spring Research

Conference, Rutgers University, New Brunswick, NJ, May 2017; “A Bayesian Cure Rate Frailty Model for

Survival Data in the Presence of Semi-Competing and Competing Risks", in Invited Session 57 on “Recent

Development on Competing and Semi-Competing Risks” at the 2017 Conference on Lifetime Data Science,

Storrs, CT, May 2017; “Bayesian Multivariate Skew Meta-Regression Models for Individual Patient Data”, at

the 2017 ICSA Applied Statistics Symposium, Hilton Chicago Downtown, Chicago, IL, June 2017; “A Partition

Weighted Kernel (PWK) Method for Estimating Marginal Likelihoods with Application” in ISBA Topic

Contributed Session 327 on “Bayesian Variable Selection”, 2017 JSM, Baltimore, Maryland, August 2017;

and “Bayesian Design of Non-Inferiority Clinical Trials via the Bayes Factor”, in an invited Session I05/TCS036

on “Innovative Trial Designs in Pharmaceutical Development”, CEN-ISBS Vienna 2017, Vienna, Austria,

August/September 1, 2017. He also delivered invited talks on “A Partition Weighted Kernel (PWK) Method

for Estimating Marginal Likelihoods with Application” in Department of Biostatistics, University of Florida,

Gainesville, FL, June 2017; “Survival Analysis Adjusting for Treatment Switch as well as Joint Modeling with

Longitudinal Data” in Boehringer Ingelheim Pharmaceuticals, Inc. at Shanghai, China, July 2017; and

“Bayesian Design of Non-Inferiority Clinical Trials via the Bayes Factor” in CDRH, U.S. Food and Drug

Administration, Silver Spring, Maryland, August 2017.

Ming-Hui Chen is a Co-PI of NIH R01 grant on “Bayesian Approaches to Model Selection for Survival Data”

for 2016-2021; NIH P01 grant on “Statistical Methods for Cancer Clinical Trials” for 2015-2020; NIH R01NR

grant on “Multi-Omics Analysis of Pain/Stress Impact on Neurodevelopment in Preterm Infants” for 2017-

2021; and NIH R01 grant on “Metabolomics Tools for Biomedicine” for 2015-2019. He is a Co-PI on an NSF

grant on “Estimating the Bayesian Phylogenetic Information Content of Systematic Data” for 2014-2018

and an American Cancer Society grant on “Activatable Nanoparticles for Radiotherapy of Metastatic

Ovarian Cancer” for 2015-2019. He is a Co-PI (PI: George Bollas) of the UConn Provost Academic Plan grant


Grants

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on “Bayesian Design of Tests for Fault Detection and Isolation in Complex Systems” for 2016-2019 and a

Co-PI (PI: Xiuling Lu) of another UConn Provost Academic Plan grant on “Polymer-Based Nanocarrier

Platform for Improving Efficacy and Safety of Potent Chemotherapeutic Agents” for 2015-2018. He is the

PI on the subcontract from UNC of Amgen grant on “Bayesian Methods for Meta-analysis”, 1/1/2014-

12/31/2017 and Merck & Co grant on “Bayesian Methods for Design and Analysis of Clinical Trials” for 2015-

2018. He is a Co-PI (PI: Xiaojing Wang) of Sanofi US Services Inc. grant on “Development of Statistical

Methodology for Identifying Respondent Subgroups Using Biomarker Signature”, 05/23/2016-08/31/2018.

He is the PI of Keter Environmental Services, Inc. grant on “Conducting an in-depth Statistical Study of

Existing Data and Formulating a Model-based Method of Determining ‘Fair Share’ Tenant Rate”. He was a

PI on a grant from Mott Corporation on “Development of a Data-Driven Approach for Forcasting”,

1/6/2017-7/22/2017.

Ming-Hui Chen was a reviewer of the grant proposals of the Research Grant Council (RGC) of Hong Kong

(2013 – 2017). � Served as the Co-Chair of the Scientific Program Committee, the 10th ICSA International

Conference, Shanghai, China, December, 19-22, 2016 and the Co-Chair of the Local Organizing Committee,

the LIDA Conference on Data Science, Precision Medicine and Risk Analysis with Lifetime Data, University

of Connecticut, Storrs, CT, May 24-27, 2017. � President Elect Appointee to serve on the Committee on

Nominations, American Statistical Association for 2016-2017. � Serves as a member of the International

Advisory Committee for the discipline of statistics of Shanghai Jiaotong University, 2013 -- present. � Chair-

Elect of the Eastern Asia Chapter of International Society for Bayesian Analysis for 2017-2018 and President-

Elect of the New England Statistical Society for June 1, 2017 - May 31, 2020.

Wu, J., Ibrahim, J.G., Chen, M.-H., Schifano, E.D., & Fisher, J.D. (2017). Bayesian Modeling and Inference

for Nonignorably Missing Longitudinal Binary Response Data with Applications to HIV Prevention

Trials. Statistica Sinica. In press.

Li W., Chen, M.-H., Wang, X., & Dey, D.K. (2017). Bayesian Design of Non-Inferiority Clinical Trials via the

Bayes Factor. Statistics in Biosciences. In press.

Royce, T.J., Chen, M.-H., Wu, J., Loffredo, M., Renshaw, A.A., Kantoff, P.W., & D'Amico, A.V. (2017). A

Comparison of Surrogate Endpoints for All Cause Mortality in Men with Localized Unfavorable

Risk Prostate Cancer. JAMA Oncology, 3, 652-658.

Zhang, D., Chen, M.-H., Ibrahim, J. G., Boye, M. E., & Shen, W. (2017). Bayesian Model Assessment in

Joint Modeling of Longitudinal and Survival Data with Applications to Cancer Clinical Trials.

Journal of Computational and Graphical Statistics, 26, 121-133.

Outreach


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Chen, M.-H., Kuo, L., & Lewis, P.O. (2014). Bayesian Phylogenetics: Methods, Algorithms, and Applications.

Chapman & Hall/CRC Mathematical and Computational Biology. ISBN: 978-1466500792.

Chen, M.-H., Dey, D.K., Müller, P., Sun, D., & Ye, K. (2010). Frontiers of Statistical Decision Making and

Bayesian Analysis --- In Honor of James O. Berger. Springer-Verlag. ISBN 978-1-4419-6943-9.

Ibrahim, J.G., Chen, M.-H., & Sinha, D. (2001). Bayesian Survival Analysis. Springer-Verlag, ISBN 0-387-

95277-2.

Chen, M.-H., Shao, Q.-M., & Ibrahim, J.G. (2000). Monte Carlo Methods in Bayesian Computation.

Springer-Verlag, ISBN 0-387-98935-8.

Petruccelli, J.D., Nandram, B., & Chen, M.-H. (1999). Applied Statistics for Engineers. Text Book, Prentice-

Hall, INC., ISBN 0-13-565953-1.

Associate Editor for Applied Stochastic Models in Business and Industry.

Zhiyi Chi gave an invited talk at the 2016 International Workshop on Applied Probability, Toronto, Canada.

Published Books

Zhiyi Chi Professor,

Associate Head, Director of Graduate

Program

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Member of the Scientific Program Committee and Session Organizer for the 8th International Workshop in Applied Probability – IWAP 2016, Toronto, Canada, June 20-23, 2016.

Chi, Z. (2015). Strong renewal theorems with infinite mean beyond local large deviations. Ann. Appl. Probab.

25, 1513--1539.

Sinha, A., Chi, Z., & Chen, M.-H. (2015). Bayesian inference of hidden Gamma process Cox model for survival

data with ties. Statist. Sinica. 25, 1613-1635. doi:10.5705/ss.2012.351.

Chi, Z. (2014). Nonnormal small jump approximation of infinitely divisible distributions. Adv. in Appl. Probab.

46, 963-984.

Chi, Z. (2012). On exact sampling of nonnegative infinitely divisible random variables. Adv. in Appl. Probab.

44, 842-873.

Editor-in-chief, Sankhya, series A and Series B, The Indian Journal of Statistics, published through Springer.

Modeling and Analysis of Large Insurance Claim and Occurrence Data: A Partnership Between UConn and

Travelers. Training grant for Travelers Companies, partially supporting four Ph.D. students as research

assistants and five faculty members within the Department of Statistics.


Dipak Dey Distinguished

Professor

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Grants

Outreach

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Member, Core Research Group of the Center for Health Communication and Marketing � Member,

Advisory Committee of the Center for Environmental Sciences and Engineering (CESE) � Member, Institute

for Collaboration on Health Intervention and Policy (In CHIP) � Fellow, Institute for Public Health Research

� Member of the Hong Kong Research Grant Council and UAE.

Presented invited talks at Social Decision Analysis Laboratory, Virginia Tech at Arlington, VA, May 2016 �

International Society for Business and Industrial Statistics conference, Barcelona, Spain, June 2016 �

International Society for Bayesian Analysis World Congress, Cagliary, Sardinia, Italy, June 2016 �

Department of Mathematics, University of Nottingham, England, September 2016 � Department of

Mathematical Sciences, University of Southampton, England, September 2016 � Department of

Mathematics, University of Glasgow, Scotland, September 2016 � Department of Economics, Heriot Watt

University, Scotland, September 2016 � Department of Mathematical Sciences, University of Southampton,

October 2016 � Department of Statistics, Kansas State University, Manhattan, KS, November 2016 � Invited

presentation at the workshop for Sankhya at the Indian Statistical Institute, Kolkata, December 2016 �

Invited Speaker, The First Eastern Asia Meeting on Bayesian Statistics, Shanghai, China, December 2016. �

Invited Speaker, The 10th ICSA international conference, Shanghai Jiao Tong University in China, December

2016 � Invited Speaker at the conference on Quantitative Methods for Public Health Researchers in SAARC

Countries, sponsored by International Statistical Institute and World Bank, Kolkata, December 2016 �

Applied Statistics Unit, Indian Statistical Institute, Calcutta, India, January 2017 � Indian Institute of

Management, Analytics group, Calcutta, India, January 2017 � Invited Speaker, ENAR meeting, Washington,

D.C., March 2017 � Invited Speaker, 2017 Conference on Lifetime Data Science: Data Science, Precision

Medicine and Risk Analysis with Lifetime Data, Storrs, CT, May 2017 � Invited Speaker, QPRC 2017: The 34th

Quality and Productivity Research Conference Quality and Statistics: A Path to Better Life, Storrs, CT, June

2017 � Keynote Speaker, 2nd International Society of Bayesian Analysis- East Asia Chapter conference,

North East Normal University, Changchun, China, July 2017.

Bharath, K., Kambadur, P., Dey, D. K., Rao, A., & Baladandayuthapani, V. (2017). Statistical tests for large

tree-structured data. Journal of the American Statistical Association. doi:

10.1080/01621459.2016.1240081

Goh, G. & Dey, D. K. (2017). Asymptotic properties of marginal least squares estimator for ultrahigh-

dimensional linear regression models with correlated errors. The American Statistician. doi:

10.1080/00031305.2017.1305359

Outreach



17

Das, S., Halder, A., & Dey, D. K. (2017). Regularizing portfolio risk analysis: A Bayesian approach.

Methodology and Computing in Applied Probability, 19(3), 865-889.

Mishra, A., Dey, D. K., & Chen, K. (2017). Sequential co-sparse factor regression. Journal of Computational

and Graphical Statistics. doi: 10.1080/10618600.2017.1340891

Dey, D.K. & Yan, J. (Eds.) (2016). Extreme value modeling and risk analysis: Methods and applications.

Chapman & Hall/CRC Press.

Upadhyay, S.K., Singh, U., Dey, D.K., & Loganathan, A. (Eds.) (2015). Current trends in Bayesian

methodology with applications. Chapman & Hall/CRC Press, 27. ISBN 13:978-1-4822-3511-1.

Editor-in-Chief of Methodology and Computing in Applied Probability � Associate Editor of Sequential

Analysis � Contracted to edit, jointly with Professor Markos Koutras, University of Piraeus, Greece, a two-

volume Handbook on Scan Statistics, to be published by Springer.

Joseph Glaz presented an invited lecture at the 8th International Workshop in Applied Probability - IWAP

2016, Toronto, Canada, June 20-23, 2016.

Published Books

Joseph Glaz Professor

Editorial Boards



outline

18

Member of the Board of International Workshops in Applied Probability (IWAP). IWAP 2016 was held on

June 20-23, 2016 in Toronto, Canada. IWAP 2018 will take place June 18-21, 2018 at Eötvös Loránd

University, Budapest, Hungary � Member of the Scientific Program Committee of the International

Symposia on Applied Stochastic Models and Data Analysis – ADMDA. ASMDA 2017 was held in London, UK

in June 2017 � Member of the oversight committee for an undergraduate minor in bioinformatics �

Affiliated faculty with Booth Engineering Center for Advanced Technology (BECATS).

Zhao, B. & Glaz, J. (2017). Scan statistics for detecting a local change in variance for two dimensional

normal data. Communications in Statistics-Theory and Methods Ser. A. 46(11), 5517-5530.

Chen, J., Glaz, J., & Sison, C. P. (2016). Monte Carlo tests for multinomial proportions. Communications in

Statistics-Theory and Methods Ser. A. 45(6), 1747-1777.

Zhao, B. & Glaz, J. (2015). Scan statistics for detecting a local change in variance for normal data with

known variance. Methodology and Computing in Applied Probability, 18, 563 – 573.

Wu, T.-L. & Glaz, J. (2015). A new adaptive procedure for multiple window scan statistics. Computational

Statistics and Data Analysis, 82, 164-172.

Glaz, J., Pozdnyakov, V., & Wallenstein, S. (Eds.) (2009). Scan Statistics: Methods and Applications.

Birkhauser, Boston.

Baeza-Yates, R., Glaz, J., Hüsler, J., & Palacios, J. L. (Eds.) (2005). Recent Advances in Applied Probability.

Springer, New York.

Glaz, J., Naus, J., & Wallenstein, S. (2001). Scan Statistics. Springer, New York.

Glaz, J. & Balakrishnan, N. (Eds.) (1999). Recent Advances on Scan Statistics. Boston, MA: Birkhauser

Publishers.

Outreach


Published Books

19

Presented invited talks at the New Researchers Conference, Johns Hopkins University, Baltimore, MD,

2017 � The New England Statistics Symposium, University of Connecticut, Storrs, CT, 2017

Gu, Y., Fan, J., Kong, L., Ma, S., & Zou, H. (2017). ADMM for high-dimensional sparse penalized quantile

regressions. Technometrics.

Gu, Y. & Zou, H. (2016). High-dimensional generalizations of asymmetric least squares regression and

their applications. The Annals of Statistics, 44(6), 2661-2694.

Associate Editor for Statistics in Medicine and Sankhya, the Indian Journal of Statistics, Series B � On the

Editorial Board of The Open Medical Informatics Journal and AIDS and Behavior.

Ofer Harel Professor

Editorial Boards

Yuwen Gu Assistant Professor



20

Presented invited talks at the Joint Statistical Meeting (JSM), Baltimore, MD, August 2017 � The 21st IAGG

World Congress of Gerontology and Geriatrics, San Francisco, CA, July 2017 � Statistics seminar Tel-Aviv

University, Tel-Aviv, Israel, June 2017 � Department of Statistics at The Hebrew University of Jerusalem,

Jerusalem, Israel, June 2017 � Department of Biostatistics, UCLA, Los Angeles CA, April 2017 � the Eastern

North American Region (ENAR) of the International Biometric Society (IBC), Washington, DC, March 2017 �

Division of Biostatistics, College of Public Health, The Ohio State University (December, 2016)

Subcontract PI on “Enhancing the Capacity of School Nurses to Reduce Excessive Anxiety in Children”

supported by Department of Education (IES) � Co-PI on “Single Cell Lineage Map (SCLM)” supported by the

University of Connecticut � Subcontract PI on “State Innovation Model/Round Two of Funding for Design

and Test Assistance,” supported by Center for Medicare & Medicaid Services via grant awarded to the State

of Connecticut Office of Healthcare advocate � Ofer also has several sub-contracts from UCHC to fund a

number of graduate students.

Elected to co-chair the International Conference for Health Policy Statistics (ICHPS), 2020 � Elected to teach

five short courses related to missing data as part of the Council of Chapters traveling courses series � Expert

reviewer, Yale Pepper Center, Yale Medical School � Member, Biostatistical Methods and Research Design

(BMRD) Study Section, Center For Scientific Review, National Institute of Health � Member, Data and Safety

Monitoring Board (DSMB) for NCCIH grant “Mobile mindfulness to improve psychological distress after

critical illness” � Member, Special Emphasis Panel - Artificial Gravity Bed Rest - AGBRESA Sensorimotor,

NASA/ESA � Member, Special Emphasis Panel - Musculoskeletal Alterations, NASA HERO Musculoskeletal

Panel; Member, Data and Safety Monitoring Board (DSMB) for NIDA grant “Behavioral intervention to

enhance HIV test/treat” � Member of the Program Committee for the 2017 meeting of the Eastern North

American Region (ENAR) of the International Biometric Society (IBS) meeting � Member of the scientific

organizing committee for the International Conference for Health Policy Statistics (ICHPS), 2018 � Mentor,

Diversity Mentoring Program, Joint Statistical Meeting, Baltimore, MD � Mentor, Math Alliance.

McGinnis, J. & Harel, O. (2016). “Multiple imputation in three or more stages.” Journal of Statistical

Planning and Inference, 176, 33-51. doi: 10.1016/j.jspi.2016.04.001.

Harel, O. & Nazzaro, V. (2016). “Re-thinking data collection for HIV prevention trials.” Journal of Acquired


Grants

Outreach


21

Immune Deficiency Syndromes, 72(4), 462-464.

Thomas, N., Harel, O., & Little, R. J. A. (2016). “Analyzing clinical trial outcomes based on incomplete daily

diary reports.” Statistics in Medicine, 35(17), 2894-2906. doi: 10.1002/sim.6890.

Jung, J., Harel, O., & Kang, S. (2016). “Fitting additive hazards model for case-cohort studies: A multiple

imputation approach.” Statistics in Medicine, 35(17), 2975-2990.

Harel, O. (2009). Strategies for data analysis with two types of missing values: From theory to application.

Saarbrucken, Germany: Lambert Academic Publishing.

Lynn Kuo is an Editor for Advances in Statistics.

Presented “Model Selection for Bayesian Nonparametric Survival Models Using Bregman Divergence

Measure” at the 2017 Conference on Lifetime Data Science: Data Science, Precision Medicine and Risk

Analysis with Lifetime Data � “Marginal Likelihoods of Phylogenetic Variable Tree Topology Models Using a

Posterior Sample” at the 10th ICSA International Conference on Global Growth of Modern Statistics in the

21st Century in December 2016.

Lynn is a biostatistician for the grant “Disparities in Breast Cancer: Is Elevated Serum sLag-3 Predictor of

More Aggressive Disease in African-American Women with Breast Cancer?” with Henry Smilowitz (PI)

Published Books

Lynn Kuo Professor

Editorial Boards


Grants

22

supported by Connecticut Breast Health Initiative 9/1/2015-8/31/2017 � Co-PI of an NSF grant “Estimating

the Bayesian Phylogenetic Information Content of Systematic Data” with Paul Lewis (PI), 2014-2018.

Member of the CDC Special Emphasis Panel ZDP1 KVA (01) of National Center for Chronic Disease

Prevention and Health Promotion to review RFA-DP-15-0020301SUPP17: Supplement to Enhance

Laboratory and Statistical Support of the Population Registry of Diabetes in Youth, 2017 � Served at the

student paper award review committee for the 31st New England Statistics Symposium, 2017 � Served at

the Program Committee for the 2017 Conference on Lifetime Data Science and organized two invited

sessions on survival analysis � Organized an invited paper session, “Novel Approaches to Genomics and

Computational Molecular Evolution,” for the 10th International Chinese Statistical Association International

Conference: Shanghai, 2016 � Treasurer of the New England Statistical Society, Inc. � Faculty advisor for the

UConn Taiwanese Student Association.

Nunez, M., Kuo, L., & Chiang, R. (2017). Managing risk-adjusted resource allocation for project time-cost

tradeoffs. Annals of Operations Research. In press. DOI: 10.1007/s1079-016-2122-7

Wang, Y.-B., Chen, M.-H., Kuo, L., Lewis, P. (2017). A new Monte Carlo method of estimating marginal

likelihoods. Bayesian Analysis. In press. DOI: 10.1214/17-BA1049.

Chen, K., Mishra, N., Smyth, J., Bar, H., Schifano, E., Kuo, L., Chen, M.-H. (2017). A tailored multivariate

mixture model for detecting proteins of concordant change among virulent strains of Clostridium

Perfringens. Journal of the American Statistical Association. In press.

Lewis, P.O., Chen, M.-H., Kuo, L., Lewis, L.A., Fučíková, K., Neupane, S., Wang, Y.-B., & Shi, D. (2016).

Estimating Bayesian phylogenetic information content, Systematic Biology.

DOI:10.1093/sysbio/syw042.

Chen, M.-H., Kuo, L., & Lewis, P. (Eds.) (2014). Bayesian phylogenetics: Methods, algorithms, and

applications. New York, NY: Chapman & Hall (CRC).

Outreach


Published Books

23

Associate Editor of Sankhya, the Indian Journal of Statistics, January 2016 - Present

Keynote Speaker and short-course at 12th Congreso Latinoamericano de las Sociedades de Estadística,

Chiclayo, Peru, October 2016 � Colloquium talk at Department of Statistics, University of Connecticut,

Storrs, CT, January 2017 � Invited Speaker at Modern Modeling Methods Conference, Storrs, CT in May

2017 � Invited Speaker at 2017 Conference on Lifetime Data Science: Data Science, Precision Medicine and

Risk Analysis with Lifetime Data, Storrs, CT, May 2017 � Invited Speaker at 1st International Conference on

Econometrics and Statistics, Hong Kong, June 2017 � Talk at Department of Statistics, Feng Chia University,

Taichung, Taiwan, June 2017 � Talk at Department of Statistics National Chung Hsing University, Taiwan,

June 2017.

Member of the scientific committee of the Model-Based Clustering and Classification (MBC2), Catania, Italy,

September 2016 � Chair of the scientific committee of the 15th Brazilian School of Regression Models (EMR

15), Goiania, Brazil, March 2017 � Member of the scientific committee of the 14th Brazilian Meeting of

Bayesian Statistics (EBEB-2018). Rio de Janeiro, Brazil, March 2018 � Member of the scientific committee

of the 4th Workshop in Survival Analysis and Applications (WASA-2017). Bahia, Brazil, March 2018.

Garay, A.W., Castro, L.M., Leskow, L., & Lachos, V.H. (2017). Censored linear regression models for

irregularly observed longitudinal data using the multivariate-t distribution. Statistical Methods in

Victor Hugo

Lachos Davila Professor

Editorial Boards


Outreach


24

Medical Research, 26, 542–566.

Galvis, D.M., Bandyopadhyay, D., & Lachos, V.H. (2017). Augmented mixed models for clustered proportion

data. Statistical Methods in Medical Research, 26, 880–897.

Lachos, V.H., Moreno, E.L., Kun, C., & Barbosa-Cabral, C.R. (2017). Finite mixture modeling of censored data

using the multivariate Student-t distribution. Journal of Multivariate Analysis, 159, 151-167.

Schumacher, L.F., Lachos, V.H., & Dey, D.K. (2017+). Censored regression models with autoregressive

errors: A likelihood-based perspective. The Canadian Journal of Statistics. DOI: 10.1002/cjs.11338

Nitis Mukhopadhyay is the Editor-in-Chief of Sequential Analysis (since 2004) � Co-Editor (jointly with Carlos

A. Coelho and Thomas Mathew) for a special issue of the Journal of Statistical Theory and Practice (JSTP)

in honor of the 70th birthday of both Professors Bimal K. Sinha and Bikas K. Sinha � Member of the Advisory

Board for SLJAS � Member, Advisory Editorial Board, Sri Lankan Journal of Applied Statistics � Associate

Editor of Communication in Statistics—Theory & Methods, Communication in Statistics—Simulation and

Computation, and Calcutta Statistical Association Bulletin.

Nitis Mukhopadhyay gave the invited plenary lecture, “Sufficiency-Ancillarity-Information: Inferences on

“Nile”-type Examples and a Common Mean” at the Probability & Statistics Day 2016: A Celebration of Bimal

Sinha’s 70th Birthday hosted by the Department of Mathematics and Statistics, University of Maryland,

Baltimore, MD, May 2016 � An invited paper in a session organized by Professor S. Zacks at the 8th

International Workshop in Applied Probability held in Toronto, Canada, June 2016 � A full length colloquium

on “Walking on a Thin Bridge Linking Teaching-Research-Teaching Excites and Rewards Me” in the UConn

Department of Statistics, November 2016 � A plenary lecture on “Non-sequential and Sequential Binomial

Sampling with Applications” at the 3rd African International Conference, University of Limpopo, South

Africa, March 2017 � An invited paper on “Sequential Binomial Sampling with Applications” at the QPRC in

the session on Sequential Methods in Quality Control (organized by Michael Baron), June 2017 � A plenary

Nitis

Mukhopadhyay

Professor

Editorial Boards



outline

25

lecture on “Recent Trends” in Sequential Estimation” at the 6th International Workshop in Sequential

Methodologies, University of Rouen, Rouen, France, June 2017.

Nitis Mukhopadhyay received travel grants from UCRF-AAUP and Taylor & Francis Group (publisher of

Sequential Analysis) to partially fund his travel to present invited talks.

Vice-President, Calcutta Statistical Association and a Member of the Council, Calcutta Statistical Association

(2010-present) � Member of the International Program Committee for the 8th International Workshop in

Applied Probability at Toronto, Canada held in June, 2016. Organizer and Chair for four invited paper

sessions � Volunteered to be mentor at the Joint Statistical Meeting in Chicago, August 2016 � Co-chair for

the 6th International Workshop in Sequential Methodologies at the University of Rouen, Rouen, France,

June 2017 � Member of the International Program Committee for the 9th International Workshop in Applied

Probability to be held in Budapest, Hungary, June 2018.

Mukhopadhyay, N. & Hu, J. (2017). Confidence intervals and point estimators for a normal mean under

purely sequential strategies involving Gini’s mean difference and mean absolute deviation.

Sequential Analysis, 36. DOI: 10.1080/07474946.2017.1319684

Mukhopadhyay, N. & Zhuang, Y. (2017). MLE, information, ancillary complement, and conditional

inference with illustrations. Methodology and Computing in Applied Probability, 19, 615-629.

Mukhopadhyay, N. & Zhuang, Y. (2016). On fixed-accuracy and bounded accuracy confidence interval

estimation problems in Fisher’s “Nile” example. Sequential Analysis, 35, 516-535.

Banerjee, S. & Mukhopadhyay, N. (2016). A general sequential fixed-accuracy confidence interval

estimation methodology for a positive parameter: Illustrations using health and safety data.

Annals of Institute of Statistical Mathematics, 68, 541-570.

Mukhopadhyay, N. & de Silva, B.M. (2009). Sequential methods and their applications. London: Chapman

& Hall/CRC. ISBN: 13:978-1-58488-105-5

Grants

Outreach


Published Books

26

Mukhopadhyay, N. (2006). Introductory statistical inference. Marcel Dekker (Taylor & Francis Group).

ISBN: 13:978-1-57444-613-5

Mukhopadhyay, N., Datta, S., & Chattopadhyay, S. (2004). Applied sequential methodologies. Marcel

Dekker (Taylor & Francis Group). ISBN: 0-8247-5395-X

Mukhopadhyay, N. (2000). Probability and Statistical Inference. Marcel Dekker (Taylor & Francis Group).

ISBN: 0-8247-0379-0.

Vladimir Pozdnyakov is an Associate Editor of Journal of Mathematical Analysis and Applications.

Vladimir Pozdnyakov gave the following invited talks this year: “Discretely Observed Brownian Motion

Governed by a Telegraph Process: Estimation,” at the 8th International Workshop on Applied Probability,

June 2016, Toronto, Canada and at the 34th Quality and Productivity Research Conference, June 2017,

Storrs, CT.

Member of the Scientific Program Committee and Session Organizer for the 8th International Workshop in

Applied Probability – IWAP 2016, Toronto, Canada, June 20-23, 2016.

Pozdnyakov, V. & Steele, J. M. (2016). Buses, bullies and bijections, Mathematics Magazine, 89, 167-176.

Vladimir

Pozdnyakov Professor




outline

Outreach

Editorial Boards

27

Chi, Z., Pozdnyakov, V., & Yan, J. (2015). On expected occupation time of Brownian bridge. Statistics and

Probability Letters, 97, 83-87.

Yan, J., Chen, Y., Lawrence-Apfel, K., Ortega, I. M., Pozdnyakov, V., Williams, S., & Meyer, T. (2014). A

moving-resting process with an embedded Brownian motion for animal movements. Population

Ecology, 56, 401-415.

Pozdnyakov, V., Meyer, T., Wang, Y., & Yan, J. (2014). On modeling animal movements using Brownian

motion with measurement error. Ecology, 95, 247-253.

Co-Editor-in-Chief of the International Statistical Review, January 2016 - Present � Associate Editor of the

Journal of Forecasting

Presented “Dynamic Models for Multivariate Time Series of Counts” at Rice University (February 2017), UC

Riverside (April 2017), the Spring Research Conference at Rutgers University (May 2017), and the

International Society of Business and Industrial Statistics (ISBIS) at IBM Watson Research, Yorktown Heights

(June 2017). She presented “Modeling Inter-event Financial Durations using Martinglae Estimating

Functions” at Virginia Tech (April 2017) and “Dynamic and Static Statistical Approaches for Transportation

Data” at the Federal HighWay Administration (FHWA, May 2017). “Fast approximate Bayesian analysis of

multivariate count time series with a marketing application” was presented at JSM 2016 in Chicago, IL

(August 2016), and “Dynamic Modeling of Transportation Data” was presented at SAMSI Summer Program

on Transportation Statistics in Durham, NC (August 2017).

Nalini

Ravishanker Professor

Editorial Boards


28

Co-P.I. with John Ivan (Civil and Environmental Engineering), and Rebecca Townsend, (Manchester

Community College) on a Year 25 New England University Transportation Center Grant, Social Network

Effects on Attitudes about Pedestrian Street Crossing Behavior, 2015 -2017. She also received a grant from

NSF for student support at the Quality and Productivity Research Conference 2017 (www.qprc2017.org).

President of the International Society of Business and Industrial Statistics (2017-2019). She is the Vice

President for Education of the New England Statistical Society. She continues to serve as the statistics

faculty coordinator for the UConn Early College Experience Program (www.ece.uconn.edu).

Harvill, J., Kohli, P., & Ravishanker, N. (2017). Clustering of nonlinear and nonstationary time series using

BSLEX. Methodology and Computing in Applied Probability, 19(3), 935-955.

Wang, K., Ivan J. N., Ravishanker, N., & Jackson, E. (2017). Multivariate Poisson lognormal modeling of

crashes by type and severity on rural two lane highways. Accident Analysis and Prevention, 99, 6-

19.

Thavaneswaran, A., Ravishanker, N., & Liang, Y. (2015). Generalized duration models and inference using

estimating functions. Annals of the Institute of Statistical Mathematics, 67, 129-156.

Ravishanker, N., Venkatesan, R., & Hu, S. (2015). Dynamic models for time series of counts with a

marketing application. In R. Davis, R. Lund, S. Holan, & N. Ravishanker (Eds.), Handbook of

Discrete-Valued Time Series. New York, NY: Chapman & Hall/CRC.

Davis, R. A., Holan, S. H., Lund, R. & Ravishanker, N. (2016). Handbook of discrete-valued time series. New

York, NY: Chapman & Hall/CRC.

Ravishanker, N., & Dey, D. (2002). A first course in linear model theory. New York, NY: Chapman Hall/CRC.

Grants

Outreach


Published Books

29

Elizabeth Schifano presented invited talks at the Institute for Operations Research and the Management

Sciences (INFORMS) Annual Meeting, Nashville, TN, November 2016, the International Chinese Statistical

Association (ICSA) International Conference, Shanghai Jiao Tong University, Shanghai, China, December

2016, and the International Society of Business and Industrial Statistics Conference, Yorktown Heights, NY,

June 2017. She was also an invited speaker at the Department of Statistics, Pennsylvania State University,

State College, PA, September 2016.

Elizabeth Schifano is currently a co-investigator on a grant funded by Travelers Insurance entitled

“Modeling and Analysis of Large Insurance Claim and Occurrence Data: A partnership between UConn and

Travelers Insurance” with PI Dipak Dey (2017-2018). She is also a co-investigator in an American Heart

Association study with PI Beth Taylor, entitled “Near Infrared Spectroscopy (NIRS) to Diagnose Statin

Myopathy” (2017-2019). With co-PIs Kun Chen and Jun Yan, Elizabeth was also awarded a grant funded by

the University of Connecticut entitled “Data Science Lab: Real World Data Science Problems Meet Future

Data Scientists” (2017-2018).

Elizabeth Schifano is an elected member of the Applied Public Health Statistics Section Council of the

American Public Health Association (APHA).

Schifano, E. D., Wu, J. Wang, C., Yan, J., & Chen, M.-H. (2016). Online updating for inference in the big

data setting. Statistics and Its Interface, 9(4), 399–414.

Elizabeth

Schifano Assistant Professor


Grants

Outreach


30

Schifano, E. D., Wu, J., Wang, C., Yan, J., & Chen, M.-H. (2016). Online updating for inference in the big

data setting. Technometrics, 58(3), 393–403.

Sofer, T., Schifano, E. D., Hoppin, J. A., Hou, L., & Bacarelli, A. (2013). A-clustering: A novel method for the

detection of co-regulated methylation regions, and regions associated with exposure.

Bioinformatics, 29(22), 2884-2891.

Schifano, E. D., Li, L., Christiani, D. C., & Lin, X. (2013). Genome-wide association analysis for multiple

continuous secondary phenotypes. American Journal of Human Genetics, 92(5), 744-759.

Richard Vitale is on the Editorial Board of Methodology and Computing in Applied Probability.

In 2016, Richard Vitale gave an invited talk on “Gaussian Processes and Convex Geometry” at the

International Workshop on Applied Probability – 2016, Toronto, Canada.

Fresen, D., & Vitale, R.A. (2014). Concentration of random polytopes around the expected convex hull.

Electronic Communications in Probability, 19(59), 1–8.

Vitale, R.A. (2010). Convex bodies and Gaussian processes. Image Analysis and Stereology. 29, 13–19.

Rubin, H., & Vitale, R. A. (1980). Asymptotic distribution of symmetric statistics. Ann. Statist., 6, 165-170.

Artstein, Z., & Vitale, R. A. (1975). A strong law of large numbers for random compact sets. Ann. Probab.

3, 879-882.

Richard

Vitale Professor

Editorial Boards



31

HaiYing Wang gave the invited talk “Informative Subdata Selection for Big Data Regression” at the ICSA-

Canada Chapter 2017 Symposium, Vancouver, BC, Canada, August 2017 and the China National Institute of

Standardization, Beijing, China, June 2017. He gave the invited talk “Information Based Optimal Subdata

Selection for Big Data Linear Regression” at the ICSA China Conference: Focus on Lifetime Data Science,

Jilin, China, July 2017; the IMS-China International Conference on Statistics and Probability, Nanning, China,

June/July 2017; the Academy of Mathematics and Systems Science, Beijing, China, June 2017; and Capital

Normal University, Beijing, China, June 2017.

Principal investigator of Simons Foundation Collaboration Grant (09/01/2017-08/31/2022).

Taught a short course entitled, “Statistical Inference for Big Data,” at Qingdao University, Qingdao, China, June 2017.

Zhang, X., Wang, H., Ma, Y., & Carroll, R. J. (2017). Linear model selection when covariates contain errors.

Journal of the American Statistical Association. doi:10.1080/01621459.2016.1219262.

Wang, H., Zhu, R., & Ma, P. (2017). Optimal subsampling for large sample logistic regression. Journal of

the American Statistical Association. doi:10.1080/01621459.2017.1292914.

Wang, H., Li, Y., & Sun, J. (2015). The focused and model average estimation for panel count data.

Scandinavian Journal of Statistics, 42, 732-745.

HaiYing

Wang Assistant Professor


Grants

Outreach


32

Wang, H., Zou, G., & Wan, A. T. K. (2012). Model averaging for varying-coefficient partially linear

measurement error models. Electronic Journal of Statistics, 6, 1017-1039.

PI on a research grant from Sanofi-Aventis, U.S., for “Development of Statistical Methodology for Identifying

Respondent Subgroups Using Biomarker Signature” from 05/23/2016 to 08/22/2017 � Serves as a Co-PI on

a research training grant from The Travelers Companies for “Modeling and Analysis of Large Insurance

Claim and Occurrence Data: A Partnership Between UConn and Travelers."

Member of the Committee on Membership Retention and Recruitment for American Statistical Association

from 2016 to 2018 � Organizing Committee of 34th Quality and Productivity Research Conference, June

2017 � Invited Session Organizer for International Society for Business and Industrial Statistics 2017

Meeting, June 2017.

Li, W., Chen, M.-H., Wang, X., & Dey, D. K. (2017). Bayesian design of non-inferiority clinical trials via the

Bayes factor. Statistics in Biosciences, in press.

Wang, X., Wei, Z., & Conlon, E. (2017). Parallel computing methods for Bayesian dynamic item response

models in educational testing. Stat, in press.

Wang, X., & Berger, J. O. (2016). Estimating shape constrained functions using a new class of Gaussian

processes. Journal on Uncertainty Quantification, 4(1), 1-25.

Xie, Y., Wang, X., & Silander, J. A. (2015). Autumn phenology of deciduous forest communities respond to

temperature, rainfall patterns, drought implying for complex climate change impacts.

Proceedings of the National Academy of Sciences of the United States of America, 112(44), 13585-

13590.

Xiaojing

Wang Assistant Professor

Grants

Outreach


33

Jun Yan is an Associate Editor of Ecological and Environmental Statistics.

Balancing the Bias-Variance Tradeoff in Extreme Value Modeling with Application to Return Level Mapping,

08/31/2017, Center for Mathematical Research, University of Montreal � Stagewise Generalized Estimating

Equations with Grouped Variables, 03/02/2017, Department of Mathematics and Statistics, Boston

University � Online Updating Method with New Variables for Big Data Streams, 10/12/2016, Department of

Statistics and Biostatistics, Rutgers University.

PI of NSF DMS 1521730 “Fingerprint Methods for Detection and Attribution of Changes in Climate Extremes

with Spatial Estimating Equations.” PI of contract with Environment Canada, "Event Attribution with Spatial

Modeling of Extremes Values."

Editor of LIDA-IG Newsletter, the newsletter of the Lifetime Data Analysis Interest Group of the American

Statistical Association � Chair of the organizing committee of the 31st New England Statistics Symposium �

Co-Chair of the Local Organizing Committee, the LIDA Conference on Data Science, Precision Medicine and

Risk Analysis with Lifetime Data, University of Connecticut, Storrs, CT, May 24-27, 2017.

Jun Yan Professor

Editorial Boards


Grants

Outreach



outline

34

Bader, B., Yan, J., & Zhang, X. (2017). Automated selection of r for the r largest order statistics approach

with adjustment for sequential testing. Statistics and Computing, 27(6), 1435-1451.

Wang, Z., Jiang, Y., Wan, H., Yan, J., & Zhang, X. (2017). Detection and attribution of changes in extreme

temperatures at regional level. Journal of Climate, 30(17), 7035-7047.

Xu, G., Chiou, S., Huang, C.-Y., Wang, M.-C., & Yan, J. (2017). Joint scale-change models for recurrent

events and failure time. Journal of the American Statistical Association, 112, 794-805.

Wang, C., Chen, M.-H., Schifano, E., Wu, J., & Yan, J. (2016). Statistical methods and computing for big

data. Statistics and Its Interfaces, 9(4), 399-414.

Dey, D. K., & Yan, J. (Eds.). (2015). Extreme value modeling and risk analysis: Methods and applications.

New York, NY: Chapman & Hall/CRC.

Yuping Zhang is a member of the editorial board of Frontiers in Bioinformatics and Computational Biology.

ICSA Applied Statistics Symposium, Chicago, Illinois, June 2017 � 1st International Conference on

Econometrics and Statistics, Hong Kong, China, June 2017 � Conference on Lifetime Data Science, Storrs,

Connecticut, May 2017 � The 31st New England Statistics Symposium, Storrs, Connecticut, April 2017 � The

10th International Chinese Statistical Association International Conference on Global Growth of Modern

Statistics in the 21st Century, Shanghai, China, December 2016.

Published Books

Yuping Zhang Assistant Professor

Editorial Boards


35

University of Connecticut Research Excellence Program Award (PI) � University of Connecticut Scholarship

Facilitation Fund (PI).

Grant panelist for Alzheimer’s Association Research Grant Program, 2017 � IBM Best Paper Award and

Liberty Mutual Best Poster Award Committee Chair, the 31st New England Statistics Symposium, 2017 �

Young Researcher Award Committee, The 10th International Chinese Statistical Association International

Conference on Global Growth of Modern Statistics in the 21st Century, 2016.

Zhang, Y. & Ouyang, Z. (2017). Joint principal trend analysis for longitudinal high-dimensional data.

Biometrics. doi:10.1111/biom.12751

Zhang, Y., Ouyang, Z., & Zhao, H. (2017). A statistical framework for data integration through graphical

models with application to cancer genomics. The Annals of Applied Statistics, 11(1), 161-184.

Zhang, Y., Linder, M. H., Shojaie, A., Ouyang, Z., Shen, R., Baggerly, K. A., Baladandayuthapani V., & Zhao,

H. (2017). Dissecting pathway disturbances using network topology and multi-platform genomics

data. Statistics in Biosciences. doi:10.1007/s12561-017-9193-0.

Zou, C., Zhang, Y., & Ouyang, Z. (2016). HSA: integrated multi-track Hi-C data modeling for genome-scale

reconstruction of 3D chromatin structure. Genome Biology, 17: 40.

Grants

Outreach


36

By Ming-Hui Chen

The Statistical Consulting Services (SCS) had

another busy and productive year. In the fall

2016, the SCS team consisted of Abhiskek Bishoyi,

Sarah Crothers, Ved Deshpande, Yeongjin Gwon,

Yujing Jiang, Hao Li, M. Henry Linder, Paul

McLaughlin, Aditya Mishra, Chen Zhang, and Fan

Zhang. In spring 2017, Gregory Vaughan and Yan

Zhang joined the team in addition to those who

had worked in the SCS while Yujing Jiang left the

SCS for the other assignment. During the

academic year, the SCS was jointly funded by

Office of the Vice President for Research (OVPR),

Dean’s Offices of CLAS and CAHNR, School of

Pharmacy, and Department of Statistics. In spring

2017, one full consulting project (1 full GA, 20

hours per week) was supported by UConn

Facilities Operations & Building Services. This

project has also been extended to the fall 2017

semester with the same amount financial

support from UConn Facilities Operations &

Building Services. With the support from the

Department of Statistics, SCS offered full-

consulting project and walk-in services in June,

July, and August 2017. Wei Shi and Yan Zhang

were the two graduate assistants who provided

statistical consulting services in the summer.

Sarah had been working in the SCS in the summer

as well. In addition, a full consulting project (1 full

GA, 20 hours per week) was supported by Mott

Corporation.

In fall 2016, SCS provided three types of full-

consulting project service, walk-in services, and

online services. Walk-in services with 17 and 16.5

walk-in hours per week in fall 2016 and spring

2017, respectively, were held in AUST 340. Two

graduate assistants were assigned to provide

online services. In the fall 2016, we had 10 full-

consulting projects and provided our walk-in

consulting services to 32 clients and online

services to 15 clients. In spring 2017, the SCS

provided services to 26 clients for full-consulting

projects, 73 clients for walk-in services, and 19

clients for online services. In summer 2017, SCS

provided services to 3 clients for full-consulting

projects and 33 clients for walk-in services.

SCS hosted a second round of workshops in the

fall semester of 2016. The first workshop section

was a two-hour session held on Wednesday,

October 26, 2016 and it covered introductory

material to power analysis and sample size

calculation. The second workshop section was a

two-hour session held on Wednesday,

November 16, 2016 and it covered survey

design.

• Where: Austin (AUST) 105

• Session 1: Power Analysis and Sample

Size Calculation: 3:30pm-5:30pm,

Wednesday, October 26, 2016

• Session 2: Survey Design: 3:30pm-

5:30pm, Wednesday, November 16,

2016

• Who: Any UConn or UCHC faculty,

students, or affiliated persons are

welcome to attend.

From the Director of the

Statistical Consulting Services

(SCS)

37

• Total Enrollments

Power Analysis and Sample Size

Calculation: 60

Survey Design: 69

In the spring semester 2017, SCS offered a series

of 3 workshop sections entitled “Introduction to

R”, “Introduction to R graphics with ggplot2”,

and “Basic Statistical Analysis in R”, which were

held on April 12, 19, and 26, 2017 respectively.

About 30 participants attended each workshop

section. Paul McLaughlin, Ved Deshpande, and

Fan Zhang prepared and presented these three

workshop sections, respectively.

On May 10, 2017, SCS launched the second

annual workshop with a series of three sessions

that cover model selection and dimension

reduction in high-dimensional data, statistics for

collaborative research grants, and repeated

measure analysis. The first and last session

provide an overview of each topic and a hands

on, live demonstration of actual case studies and

the second session is on how to develop a

comprehensive Statistical considerations section

for an external National Institute of Health (NIH)

R01 research grant when collaborating with

statisticians.

Session 1 Presenter on May 10

Session 2 Presenter on May 10

• Location: Laurel Hall 201

• Date: Wednesday, May 10, 2017

• Sessions:

1. Model Selection and Dimension

Reduction: Dealing with High-

Dimensional Analysis

2. Statistics for Collaborative Research

Grants-Strategies for Power Analysis and

Statistical Plans

3. An Overview of Repeated Measure

Analysis

Lunch was provided to all participants in the

Union Street Market (USM). All participants

picked up lunch cards during registration on May

10th. About 70 participants attended this

workshop. Our PhD student Gregory Vaughan

presented the first session, and Dr. James Grady,

Director of the Biostatistics Center for the

Connecticut Institute for Clinical and

Translational Science (CICATS) at the University of

Connecticut and Professor in the School of

Medicine, delivered the second session. The third

session was co-presented by our own PhD

students, Chen Zhang and Yeongjin Gown.

Yeongjin was also the overall coordinator of the

second SCS annual workshop.

38

Session 3 Co-Presenters on May 10

Pfizer Global Research & Development Student

Fellowship Program (December 2007 - Summer

2018)

In December 2007, the Department of Statistics

at University of Connecticut and the Global

Research & Development of Pfizer Inc. signed a

joint agreement to develop a Fellowship

program. Wangang Xie was the first Student

Fellow. Under the agreement, he worked at

Pfizer 10 hours each week in spring 2008 and 20

hours each week in summer and fall 2008. In

November 2008, the Department of Statistics at

the University of Connecticut and the Global

Research & Development of Pfizer Inc. signed a

joint agreement for the extension of the

Fellowship program. Miaomiao Ge became the

second Student Fellow under this agreement.

This agreement was extended several times. Ms.

Ge was the Student Fellow until August 2011. In

fall 2011 to fall 2014, Ouyang Guang was the third

Pfizer Student Fellow. Jing Wu became the fourth

Pfizer Student Fellow in spring 2015. Ms. Wu

worked as a student fellow at Pfizer in the 2015-

2016 academic year and continues to work in the

summer and fall of 2016 as well. Daoyuan Shi was

the student fellow at Pfizer in spring and summer

2017. Pfizer has extended this fellowship

program to 2017-2018 for the academic year as

well as the summer. Lijiang Geng is the student

fellow at Pfizer in fall 2017.

Collaboration with School of Nursing (Fall 2007-

Spring 2018)

From fall 2007 to spring 2011, the School of

Nursing hired Ms. Miaomiao Ge, a Ph.D. student

of the Department of Statistics, as a half-time

student assistant under supervision of Professor

Ming-Hui Chen. In August 2011, the School of

Nursing hired Ms. Danjie Zhang as Miaomiao Ge’s

replacement. Ms. Zhang worked at the School of

Nursing 10 hours each week as a half-time

graduate assistant in 2011-2012, 2012-2013, and

2013-2014 academic years. In the 2014-2015

academic, Ms. Jing Wu replaced Ms. Danjie

Zhang. Ms. Wu worked at the School of Nursing

in the 2015-2017 academic years. The School of

Nursing has extended a half RA support for the

2017-2018 academic year. Ms. Hao Li is the

current graduate assistant, who spends 10 hours

per week in the School of Nursing.

39

By Dipak Dey Brief bio:

Prasanta Chandra Mahalanobis (born June 29, 1893, in Calcutta (now Kolkata), India —died June

28, 1972, Calcutta), was instrumental in formulating India’s strategy for industrialization in the

Second Five-Year Plan (1956–61).

Born to an academically oriented family, Mahalanobis pursued his early education in Calcutta.

After graduating with honors in Physics from Presidency College, Calcutta, in 1912, he moved to

England to study physics and mathematics at the University of Cambridge. Just before

Mahalanobis left the university in 1915, he was introduced to statistics by one of his teacher. When

he returned to India, he accepted a temporary position teaching physics at Presidency College

(now Presidency University), and he became a professor of physics there in 1922. However, his

interest in statistics had evolved into a serious academic pursuit, and he applied statistical

methods to problems in anthropology, biology and meteorology. On December 17, 1931, he

established the Indian Statistical Institute (ISI) in Calcutta.

As a Statistician, Mahalanobis is most known for the development of a measure of comparison

between two data sets which is known as the Mahalanobis distance. He also introduced innovative

techniques for conducting large-scale sample surveys and calculated acreages and crop yields by

using the method of interpenetrating sub sampling. He devised a statistical method called fractile

graphical analysis, which could be used to compare the socioeconomic conditions of different

groups of people. He also applied statistics to economic planning for flood control. With the

objective of providing socioeconomic statistics, Mahalanobis established the National Sample

Survey Organization in 1950 and also set up the Central Statistical Organization to coordinate

statistical activities in India. He was also a member of the Planning Commission of India from 1955

to 1967. The Planning Commission’s Second Five-Year Plan encouraged the development of heavy

industry in India and relied on Mahalanobis’s mathematical description of the Indian economy,

which later became known as the Mahalanobis model.

Mahalanobis held several national and international portfolios. He served as the chairman of

the United Nations Sub-Commission on Sampling from 1947 to 1951 and was appointed the

honorary statistical adviser to the government of India in 1949. For his pioneering work, he was

awarded the Padma Vibhushan, one of India’s highest honors, by the Indian government in 1968.

On His 125th Birth Anniversary,

Reminiscence of Prasanta Chandra

Mahalanobis and His Impact in

Today’s Statistical Science

40

My days at ISI:

At the young age of 17 when I joined ISI, some elements of the fabric of ISI looked bizarre to me.

Soon after I joined with bunch of my fellow students, we were told that we had one of the largest

library in Asia with many books and journals in Mathematics, Statistics, Economics and many other

subjects. We were also told that there was a computer center with main frame computing

(Honeywell 480). Perhaps that was the first computer in India for civilians’ use. Soon after I realized

that, ISI had three types of people, students like us, Professor Mahalanobis (he used to be known

as simply the Professor) and rest of the people were all workers. Surprisingly, we students also

found that there were only around 150 students combining B. Stat. and M. Stat. and approximately

400 professors and research scholars in ISI. Also besides Statistics, there were various units, e.g.,

Anthropometry, Biometry, Chemistry, Computer Science, Economics, Geological Science, Human

Genetics, Plant science, Physics, Psychometry, Sociology, Zoology and so on.

The whole affair seemed to me like a small town that was attempting to be self-sufficient and self-

reliant, which seemed to be quite odd to us students. Why on earth should there be so many units

and we had to take so many courses outside statistics? Of course that became clear when I was in

B. Stat 4th year and I had a course called “Application of Statistics to Sciences”.

Is Statistics a branch of Probability?

In one of the fine winter morning in 1971, suddenly Professor came to our Statistical methods

class. He gave a nice presentation on applications of Statistics with lots of examples followed by a

lecture on probability. Then the question came, Is Statistics a branch of Probability? We were told

to write our answers on a piece of paper, which were collected by Professor at the end of class.

We found that was a small survey and realized much latter the value of that question. Actually it

was a kind of tricky question. In my perspective, Statistics is primarily a branch of applied

mathematics, which tries to make sense of data in the real world whereas, Probability is primarily

a theoretical branch of mathematics, which studies the consequences of events. Both subjects are

important, relevant, and useful. But they are different, and understanding the distinction is crucial

in properly interpreting the relevance of analytical evidence.

Statistics as a Key Technology:

At the 125th American Statistical Association Meeting, Mahalanobis gave a speech entitled,

“Statistics as a key technology”, which was echoed at the 1971 convocation in ISI, Kolkata. In his

speech, Mahalanobis highlighted the need of reliable statistics is as great or even greater today

for the rapid economic growth of all the countries. In his talk, he emphasized the strong need of

applications of mathematical statistics and probability to real world problems. Mahalanobis

mentioned,” Science can advance only through a careful accumulation of facts and observations

and critical study of their inter-relations which have their foundation in nature itself and which

cannot be changed or upset by any human authority however high”. This lecture motivated many

of us in the era of development of statistical sciences through cross disciplinary and

interdisciplinary research.

41

ISI and Sankhya:

Perhaps the two most important contributions by Mahalanobis, other than his scientific papers,

were setting up the ISI and the founding of the journal Sankhya. The ISI began life in around 1920

as an unofficial group working on statistical problems in Presidency College. It soon acquired the

name of the Statistical Laboratory and was located in Mahalanobis's room in the Physics

Department. It was formally "registered on 28 April 1932 as a non-profit distributing learned

society under the Societies Registration Act XXI of 1860. Basically through the 1920s and up to

1931 almost all statistical work done in India was by Mahalanobis. However, after setting up the

ISI, as Director and Secretary on 17th December, 1931, he started building up the Institute with

new appointments. For example, in December 1932 Mahalanobis offered R C Bose a part-time

post at the Indian Statistical Institute and S N Roy who had been appointed to a part-time post a

few months after Bose. Today, ISI has centers in Delhi, Chennai, Bangalore, Hyderabad, Mumbai,

and the north east center at Tezpur and experimental stations at Giridih, Jharkhand. They all

operate at different educational and research levels.

The other major achievement of Mahalanobis was the founding of the statistics journal Sankhya in

1933 as a publication of the Indian Statistical Institute. I quote from Mahalanobis's own words,

“Those of us who are actively engaged in starting this journal are doing so because of our interest

in statistics and our belief that a journal devoted to statistics will be useful in India. ... The spirit and

outlook of 'Sankhya' will be universal, but its form and content must necessarily be, to some extent,

regional. We shall keep the special needs of India in view without, however, restricting the scope

of the journal in any way. We shall naturally devote closer attention to the collection and analysis

of data relating to India, but we shall try to study all Indian questions in relation to world problems.

A research journal serves that narrow borderland which separates the known from the unknown,

and it is not always possible to see clearly the lines of future developments. We shall, therefore,

invite papers of all kinds appraising them only on the basis of observational accuracy and logical

reasoning…..”

Mahalonobis’ in today’s big data era:

Digital data are increasingly changing the shape of our world. In an era with a plethora of cheap,

vast data in which buzzwords such as Big Data, data analytics, and data mining have been

integrated into the common vernacular, it is worth to be noted that Mahalanobis distance is still

of paramount important in various statistical problems, e.g., sparse reduced rank multivariate

regression, high dimensional factor analysis model, clustering and classification. Functional

Mahalanobis distance is being used for outlier detection, influential diagnostics etc.

In recent years, Mahalanobis distance being heavily used in computer vision. A common usage in

computer vision systems is for comparing feature vectors whose elements are quantities having

different ranges and amounts of variation, such as a 2-vector recording the properties of area and

perimeter. Also learning for large margin nearest neighbor classification and learning a

Mahalanobis distance based dynamic time warping measure for multivariate time series

classification are one of current interest. Application of Mahalanobis distance metric for data

clustering and classification in pattern recognition and in machine learning are being used

42

extensively. Financial Applications of the Mahalanobis distance are also playing major role in

portfolio analysis.

In conclusion, I take this opportunity of conveying to the readers that Mahalanobis’s work will

remain immortal to our and next generation of statistical scientists. His influence on

interdisciplinary research will exist forever.

Two Announcements:

The Indian Statistical Institute is commemorating his 125th Birth Anniversary in 2017-18.

On this occasion, a conference in Statistics and Probability is being organized at the Kolkata

campus of the Institute, to be held on January 2-4, 2018. We hope you will consider joining us in

these celebrations and participate in this conference. For more information, visit:

http://www.isid.ac.in/~pcm125spconf/.

Sankhya is bringing out two special issues (Series A and Series B) celebrating the 125th birth

anniversary of PCM. For more information, please visit:

http://www.springer.com/statistics/journal/13171 and http://sankhya.isical.ac.in/index.html.

Dipak K. Dey, University of Connecticut & Editor-in-Chief, Sankhya

By Kun Chen, NESS Secretary

As we are enjoying the most beautiful season in New England, there are exciting developments

happening in our young society. The society council is formed by 15 society council members from

14 different institutions/companies over the New England area and the neighboring states

(https://nestat.org/about/council/). Five Vice-Presidents have been appointed to lead the

developments and operations of NESS in different areas, including Strategies & Development

(Joseph Cappelleri, Pfizer), Young Group (Jessi Cisewski, Yale), Education (Nalini Ravishanker,

UConn), Scientific Program (Nicholas Reich, UMass), and Journal & Publication (Min-ge Xie,

Rutgers); see details at https://nestat.org/about/structure/. More and more enthusiastic

members are getting involved in the committees organized by the five VPs.

An Update from the New

England Statistical

Society

43

We envision NESS to be an engine to mobilize the abundant pedagogical and research resources

in the New England area and beyond, and in doing so, to promote and sustain the growth and

expansion of statistical science as one of the two fundamental pillars of Data Science (the other

being computer science). With the emergence of data science and the growth of technological

innovations including social media, we see tremendous opportunities, as well as urgency, to

integrate statistical research and education. With NESS, we are able to pool our rich regional

talents to produce educational products and organize professional activities, including NESS

Distinguished Colloquium Series, short course offerings/videos, online tutorials, and special events

for young statisticians, among others. In particular, we are in the process of establishing a rather

unique journal: The New England Journal of Statistics in Data Science. It is unique because it will

focus on the roles of statistics (and statisticians) in Data Science.

I would like to take this opportunity to make a few announcements:

1. Special rate for life membership, and joint membership with Institute of Mathematical

Statistics (IMS). We are offering a founding-year special rate of $500 for NESS life

membership. Starting on January 1st, 2018, the life membership rate will be $600. You may

also get 25% off the IMS regular membership fee ($79 per year after discount) if you

register IMS through NESS. Please join us if you share our vision and want to help to make

it a reality. For more information on registration and making a donation, please visit NESS

website at http://www.nestat.org/. You may register online or send the registration form

(attached) and a check directly to NESS business address:

New England Statistical Society (Attn: Lynn Kuo)

Room 306, Philip E. Austin Building

215 Glenbrook Rd., U-4120

Storrs, CT 06269-4120

We greatly appreciate your generosity in supporting our mission.

2. 2018 New England Statistics Symposium. The 32nd New England Statistics Symposium will

be held on April 13–14, 2018 at the University of Massachusetts, Amherst, MA. The

symposium will be hosted by the Department of Mathematics & Statistics and the

Department of Biostatistics & Epidemiology, University of Massachusetts, Amherst, MA.

• Dates: Friday, April 13 – Saturday, April 14, 2018

• Location: University of Massachusetts, Amherst

• Contact:

o Nicholas G. Reich, [email protected]

o Anna Liu, [email protected]

The New England Statistics Symposium is an annual conference that moves throughout the

region. In odd-years the conference is held at the University of Connecticut. Short courses,

break-out groups, poster sessions and keynote addresses are spread over two days. In

44

recent years, there has been a student paper competition and various other sponsored

awards. For information about past symposiums, please

check www.nestat.org/history/symposium/. More details regarding the 2018 symposium

will be posted soon.

3. Celebrating the Foundations and Impact of Statistics: A Symposium Honoring the

95th Birthday of Herman Chernoff. This event is co-sponsored by NESS, ASA Boston Chapter,

and Department of Statistics at Harvard University, which will take place on May 4th at

Harvard University. More details will be posted on NESS website soon.

4. NESS Colloquium Series. Brown University will host the first colloquium of this new series.

The detailed information of the speaker, and the presentation title and abstract will be

posted at www.nestat.org as soon as they become available. We greatly appreciate the

support from the Center for Statistical Sciences and the Department of Biostatistics at

Brown.

Kun Chen, University of Connecticut & NESS Secretary ([email protected])

46

• Student Membership is free. Regular membership is $30 per year. • Special rate for life membership: We offer a founding-year special rate of $500. Starting from

January 1st, 2018, the life membership rate is $600. • Joint membership with Institute of Mathematical Statistics (IMS) is $109 per year.

Please send the form and a check to: New England Statistical Society (Attn: Lynn Kuo)

Room 306, Philip E. Austin Building 215 Glenbrook Rd. U-4120 Storrs, CT 06269-4120

Membership Registration Form

Last Name:

First Name:

Middle Name:

Membership Type: Student Regular Life NESS/IMS

If Student Members, Expected Graduation Year:

Email Address:

Phone Number:

Employer:

Address Line 1:

Address Line 2:

County/City:

State/Province:

Zip Code:

Country:

Signature & Date

48

Joseph Cappelleri Was featured on the Fall 2017 cover of Legacy Matters: The Harvard T. H. Chan School of Public Health Newsletter for Sophisticated Donors.

Ming-Hui Chen Was recognized for 15 years of service at the University of Connecticut.

Ofer Harel P.Stat – Accredited Professional Statistician by the American Statistical Association

Victor Hugo Lachos Davila Received an Honorary doctorate from the Universidad Pedro Ruiz Gallo, Lambayeque, Peru, in October 2016

Vladimir Pozdnyakov together with Michael Steele (University of Pennsylvania), received the 2017 Carl B. Allendoerfer Award for excellent mathematical writing published in the Mathematics Magazine, a journal of the Mathematical Association of America. Vladimir Pozdnyakov and Michael Steele were honored for their publication, “Buses, Bullies, and Bijections.” Vladimir also was recognized for 15 years of service at the University of Connecticut.

HaiYing Wang Received the Microsoft Azure for Research Award

Xiaojing Wang

Became an Elected Member of the International Statistical Institute

Jun Yan Elected as a 2017 Fellow of the American Statistical Association

Visiting Professors The department welcomes Visiting Assistant Professor, Néhémy Lim, and is delighted to continue the appointment of Visiting Assistant Professor, Panpan Zhang, for the 2017-2018 academic year.

49

By Elizabeth Schifano

Every year, the Department of Statistics hosts an annual Fall picnic to allow new students to get

to know the current students, faculty, staff and their families, as well as to acknowledge and

provide well-deserving students with Academic and Service Awards. Continuing with recent

tradition, the 2017 picnic was held at Patriots Park Lodge which overlooks the lovely Coventry

Lake. The Graduate Student Committee organized a wonderful afternoon with over 80 people in

attendance. It was a beautiful crisp day, made complete with delicious food, great conversation,

and a variety of games and sports. We are already looking forward to next year’s event!

50

2016-2017 Student Awards

Left to right: Wenjie Wang (Service Award), Professor Ming-Hui Chen, Yeongjin Gwon (Service Award), Yang Liu (Best Performance in Inference), Jieying Jiao (Gottfried Noether Award for Mathematical

Statistics), Yan Li (Gottfried Noether Award for Mathematical Statistics, Mark of Excellence), Lijiang Geng (Best Performance in Probability), Qingyang Liu (H. Fairfield Smith and Dolores S. Smith Award for

Excellence in Applied Statistics, Mark of Excellence), Hao Li (Service Award), Yulia Sidi (H. Fairfield Smith and Dolores S. Smith Award for Excellence in Applied Statistics), Professor Lynn Kuo, Professor Zhiyi Chi

Not pictured: Cheng Zhang (Mark of Excellence)

51

We continue to have a stream of excellent colloquia:

Robert E. Kass Carnegie Mellon University Statistical Thinking in Neuroscience

Marcos Prates Universidade Federal de Minas Gerais Where Geography Lives? A Projection Approach for Spatial Confounding

Taeryon Choi Korea University Bayesian Shape Restricted Regression Models Using Gaussian Processes Priors

Panpan Zhang University of Connecticut Joint Distribution of Nodes of Different Out Degrees and the Degree Profile in Preferential Dynamic Attachment Circuits

Yahzen Wang University of Wisconsin-Madison Quantum Computation and Statistics

Neal Thomas Pfizer, Inc. Using Meta-Analyses to Guide Statistical Methodology for Clinical Dose Response Studies

Kung-Sik Chan University of Iowa Inference for Threshold Diffusions

Kun Chen University of Connecticut On Large-Scale Predictive Modeling of Mixed and Incomplete Outcomes Joint UConn/ UMass Statistics Colloquium at the University of Massachusetts Amherst, MA

52

Sumona Mondal Clarkson University Sample Size Determination for Power Analysis Using Hierarchical Designs

Ben Shaby Penn State University Spatial Extreme Value Analysis for Fire Risk Assessment

Heping Zhang Yale University School of Public Health Statistical Strategies in Analyzing Data with Unequal Prior Knowledge

David Banks Duke University Statistical Issues with Agent- Based Models

Nitis Mukhopadhyay University of Connecticut Walking on a Thin Bridge Linking Teaching-Research-Teaching Excites and Rewards Me

Jim Booth Cornell University Table Counting and Exact Conditional Inference for Contingency Tables

Fangfang Wang University of Connecticut On the Estimation of Integrated Volatility in the Frequency Domain

Victor Hugo Lachos Davila University of Connecticut Heavy-tailed Longitudinal Regression Models for Censored Data: A Likelihood Based Perspective

Yuwen Gu University of Minnesota High-dimensional Generalizations of Asymmetric Least Squares and Their Applications

Vishesh Karwa Harvard University Differentially Private Statistical Inference

Nhat Ho University of Michigan Parameter Estimation and Multi-level Clustering with Mixture and Hierarchical Models

53

HaiYing Wang University of New Hampshire Information-Based Optimal Sub Data Selection for Big Date Linear Regression

Jon Steingrimsson John Hopkins Bloomberg School of Public Health Doubly Robust Survival Trees and Forests

Kuang-Yao Lee Yale School of Public Health On Additive Conditional Independence for High-dimensional Statistical Analysis

Gongjun Xu University of Michigan Identifying Latent Structures in Restricted Latent Class Models

Robert W. Makuch featuring Andrea B Troxel, Sc.D. New York University School of Medicine Statistics Issues in Pragmatic Behavioral Clinical Trials

Donghui Zhang Sanofi, U.S. Statistical Collaborations in Drug Discovery: Challenges and Opportunities

Xiwen Ma Sanofi, U.S. Some Statistical Issues in Biomarker Identification for Clinical Study

Bani K. Mallick Texas A & M University Bayesian Gaussian Graphical Models and their Extensions

Gen Li Columbia University A General Framework for the Association Analysis of Heterogeneous Data

54

By Ming-Hui Chen and Jun Yan

It was our great pleasure to host the 2017 Conference on Lifetime Data Analysis (LIDA) at

University of Connecticut. The conference theme was ``Data science, precision medicine and risk

analysis with lifetime data,” held at the University of Connecticut, Storrs, Connecticut, on May 25–

27, 2017. The aim of the conference was to promote and support the development and application

of statistical methods for lifetime or time-to-event data. The primary sponsor of the conference

was the LIDA Interest Group of the American Statistical Association, in which many our faculty

The 2017 Conference on

Lifetime Data Analysis at

UConn a Success

55

members are actively involved. The conference was jointly-sponsored by the International Chinese

Statistical Association (ICSA), the University of Connecticut, Bayer Pharmaceuticals, Takeda

Pharmaceuticals, and the American Statistical Association. The conference chair was Professor

Jack Kalbfleisch of University of Michigan. The program chair was Professor Mei-Cheng Wang of

Johns Hopkins University. Our own faculty members Professors Ming-Hui Chen and Jun Yan served

as co-chairs of the local organization committee, with members including our own faculty

members, Professors Dipak Dey and Elizabeth Schifano, and our student webmaster, Henry Linder.

The keynote speakers were two highly accomplished leaders in the field: Professor Niels Keiding

from the University of Copenhagen, Denmark, and Professor Lee-Jen Wei from Harvard University.

Four short courses before the technical sessions were taught by five leading experts in their

respective areas: Drs. Mitchell Gail, Joseph Ibrahim, Ruth Pfeiffer, Joanna Shih and Xiao-Hua

(Andrew) Zhou. There were 63 sessions organized by a large and very distinguished program

committee led by Prof. Mei-Cheng Wang. About 340 participants enjoyed the pleasant spring

weather at Storrs and the warm hospitality of the faculty and students of UConn. A student and

postdoctoral paper and poster award competition was held, with a review committee led by Prof.

Zhezhen Jin of Columbia University. The committee gave out three paper awards and three poster

awards. Our own student Jing Wu (PhD 2017) was one of the poster award recipients for her poster

“Online updating of survival analysis in the big data setting.”

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This was a big gathering of people working on lifetime data science, researchers and practitioners,

seniors and juniors, novices and experts. We strove to provide the best support to the colleagues

coming to the conferences from all over the world despite a limited budget and resources. The

conference started from four short courses on Thursday, May 25. With a friendly registration fee

($160 for non-student participant), we were able to provide a mixer reception on Thursday

evening, two breakfasts, one lunch at the Student Union on Friday, and one barbecue lunch on

Saturday. 120 guests joined the banquet dinner on Friday at Chang's Garden, where the authentic,

multiple-course Chinese food became a lasting memory. We are grateful to those who kindly send

us encouragingly positive feedbacks about their conference experience.

According to Professor Jack Kalbfleisch, the conference was a great success by any measure for

many participants. The success of the local organization depended on a spectacular team work.

We thank Drs. Ray Liu and Jonathan Siegel for their efforts in facilitating the sponsorship from

Takeda and Bayer, respectively. Our student webmaster, Henry Linder, did an excellent job; he

communicated closely with the program committee chair, Dr. Mei-Cheng Wang, from a very early

stage, initiated/maintained the conference website, and developed tools for the registration,

abstract submission, and program book generation. Our graduate student volunteers were the

best helpers and played a critical role to ensure the smoothness of the conference in all aspects.

The coordinator, Hao Li, successfully recruited 26 student volunteers. Under the leadership of Hao

Li, Disheng Mao, Jing Wu, Yeongjin Gwon, and Aritra Halder, they tended the registration desks

continuously for three days, provided technical support on presentations at every single session,

took photos for almost every presenter, and did many other things to make all participants to feel

warmly welcomed. We would also like to thank the UConn Statistics Department staff, Megan

Petsa, Tracy Burke, and Hannah Melroy, for their endless support and preparation for this

conference. Finally, we would like to thank Anne Hill of UConn Events & Conference Services for

having done such an outstanding job for taking care of all detailed logistics, arrangements, and

preparation for this conference. We would not have such a successful conference without her

great effort, hard work, and dedication.

We thank all participants for visiting UConn and hope they have marked UConn as an interesting

stop in their journey of lifetime data science.

Ming-Hui Chen ([email protected]), Jun Yan ([email protected])

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By Nalini Ravishanker and Haim Bar

QPRC 2017 Quality and Statistics: Path to a Better Life, was held June 13-15, 2017 at the University

of Connecticut, Storrs CT, together with a one-day short course on June 12, 2017. The co-chairs

were Haim Bar and Nalini Ravishanker. Haim Bar will be a guest editor of the upcoming special

issue of the Wiley journal Applied Stochastic Models in Business and Industry, based on talks at this

conference.

QPRC 2017 is the annual meeting of the Quality and Productivity section of the American Statistical

Association (ASA). There is a long history of successful annual QPRCs, which have provided a large

group of statisticians and inter-disciplinary professionals unique opportunities to meet and

exchange ideas related to methods relating to a broad set of topics. The conference had three

plenary speakers, Shelly Zacks, Vijay Nair, and Bill Meeker. There were several invited sessions with

strong speakers, as well as contributed sessions and poster sessions. The poster session presenters

were graduate and undergraduate students. There were parallel Technical visits to BIRC, CHASE,

and IMS at UConn which everyone enjoyed. An excellent short course on June 12 titled

Computational Bayesian Methods for Big Data Problems was offered by Steve Scott from Google

Inc. The conference was sponsored by NSF, SAS, Minitab, StatEase, TriloByte, UConn CLAS, and the

UConn Department of Statistics. Support from an NSF grant for QPRC 2017 enabled the

participation of a large and diverse group of graduate and undergraduate students, who benefited

enormously from the short course and the conference. In addition to getting an opportunity to

interact with professionals from academia, government, and industry, they were able to

disseminate their research in a poster session and secure feedback that would enhance their

future research.

All the information about the conference and short course, including the technical tour has been

archived here: http://archive.stat.uconn.edu/qprc17/

Nalini Ravishanker ([email protected]), Haim Bar ([email protected])

The Quality and Productivity Research Conference

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By Ofer Harel

The department applied and became a graduate member of the Math Alliance

(https://mathalliance.org/welcome/). The National Alliance for Doctoral Studies in the

Mathematical Sciences, now best known as the Math Alliance, was founded in 2001 as a

partnership between the math sciences departments at three Iowa State Regents universities. It

later grew to encompass mathematics departments across the U.S. and recently also Statistics

departments. There are currently 37 Doctoral programs affiliated across mathematics, statistics

and biostatistics.

Our department joined the alliance in order to increase diversity in our student population. This

year, we are working hard in order to recruit more students from commonly considered under

represented populations.

Ofer Harel ([email protected])

By Haim Bar and Jun Yan

Our department proudly hosted the 31st New England Statistics Symposium (NESS) on Saturday,

April 22, 2017. The purpose, as usual, was to bring together statisticians from all over New England

to a central location to share research, discuss emerging issues in the field, and network with

colleagues. The annual conference was started back in 1987 by our department. It is held at UConn

in odd-years and elsewhere in New England in even-years. This year, we celebrated the 30 years

of NESS since its inception. Over 250 participants attended the conference.

The 31st New England

Statistics SymposiumApril 21-22, 2017 at UConn

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On the first day, three full-day short courses were taught: Fitting mixed-effects models using the

Julia language by Douglas Bates (University of Wisconsin—Madison); Practical Integrative

Statistical Learning: Recent Developments and Case Studies by Robert Aseltine (University of

Connecticut Health Center) and Kun Chen (University of Connecticut); and Subgroup Analysis and

Treatment Scoring with Application in Precision Medicine by Menggang Yu (University of

Wisconsin—Madison). About 60 participants took the short courses.

On the second day, welcome and opening remarks were delivered by UConn’s Provost & Executive

Vice President for Academic Affairs, Jeremy Teitelbaum, CLAS associate dean, Robin Côté, and the

Head of the Department of Statistics at UConn, Ming-Hui Chen.

Two keynote speakers were Professor Xihong Lin of Harvard University and David Madigan of

Columbia University. The talks were titled “Hypothesis Testing for Weak and Sparse Alternatives

With Applications to Whole Genome Data” and “Honest Learning for the Healthcare System:

Large-scale Evidence from Real-world Data”, respectively.

During the conference, Xiao Li Meng from Harvard University announced the establishment of the

New England Statistics Society. More information on the new society can be found in this

newsletter and at http://nestat.org.

There were 24 invited sessions, including a panel discussion on careers in statistics, with 12

sessions in the morning and 12 in the afternoon. The topics of the invited sessions cover Bayesian

statistics, big data, biopharmaceutical statistics, causal inference, dependence modeling,

extremes, finance, genomics, graphical models, high dimensional data, health analytics, insurance,

machine learning, space-time models, social network, subgroup analysis, survival analysis, and

applications from many fields.

A special memorial session in honor of Stephen Feinberg, University Professor of Statistics and

Social Science at Carnegie Mellon University, was organized and chaired by Dipak Dey, entitled

“Bayesian Statistics with Applications.” The three speakers were Edoardo Airoldi of Harvard

University, Bani Mallick of Texas A&M University, and Sudipto Banerjee of University of California

Los Angeles. Professors Mallick and Banerjee are both UConn Statistics alumni.

A poster session was held during lunch. The Student Poster Award was sponsored by Liberty

Mutual, and was facilitated by our alumnus Chun Wang (PhD 2016) who works at Liberty Mutual.

There were 34 posters, and the award winners were: David Cheng from Harvard University,

Timothy Leonard from University of Rhode Island, Qiongshi Lu from Yale University, and Xinran Li

from Harvard University.

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The IBM Watson Research Lab kept sponsoring the IBM Student Paper Award. The recipients of

the award were: Wenjie Wang (University of Connecticut), Suzanne Thornton (Rutgers University-

New Brunswick), and Elizabeth Upton (Boston University).

The review committee of the Liberty Mutual Student Poster ward and the IBM Student Paper

Award, led by Professor Yuping Zhang, consisted of Jacob Bien (Cornell University), Kun Chen

(University of Connecticut), Zhiyi Chi (University of Connecticut), Forrest Crawford (Yale

University), Victor Hugo Lachos Davila (University of Connecticut), Beatriz E. Etchegaray Garcia

(IBM), Patrick Flaherty (University of Massachusetts-Amherst), Yuwen Gu (University of

Minnesota), Lynn Kuo (University of Connecticut), Kuang-Yao Lee (Yale University),

Nitis Mukhopadhyay (University of Connecticut), Vladimir Pozdnyakov (University of Connecticut),

Fangfang Wang (University of Connecticut), Haiying Wang (University of New Hampshire), Pei

Wang (Mount Sinai School of Medicine), Jun Yan (University of Connecticut), Panpan Zhang

(University of Connecticut), Yuping Zhang (University of Connecticut), and Yizhe Zhao (Cornell

University). We thank all the reviewers for their time and effort.

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The Travelers Reception, sponsored by longtime industry partner Travelers Insurance, closed the

daytime activity, during which the Liberty Mutual Student Poster Award and the IBM Student

Paper Award were presented by Xihong Lin, representatives of the sponsors, and members of the

organizing and award committees. The traditional NESS banquet was held at Sichuan Pepper in

Vernon, a famous authentic Sichuan food in the region. Approximately 60 people participated in

the banquet.

The NESS Organizing Committee consisted of Haim Bar, Kun Chen, Jun Yan, and Yuping Zhang. Bar

took over the leadership after Yan went on an unexpected medical leave. We thank our sponsors,

the ASA CT Chapter, the Department of Statistics, UConn, The Hartford, IBM Watson Lab, Liberty

Mutual, Pfizer, and Travelers Insurance. Our student volunteers played a critical role in helping the

conference proceed smoothly in all aspects. The chief student leader was Gregory Vaughan (PhD,

2017), and the subcommittee leaders were Jun Hu (sign), Wenjie Wang (IT), Yeongjin Gwon

(poster), Sedeep Bapat (registration), Jing Wu (photo), and Yishu Xue (parking). Our student

webmaster Henry Linder developed the webpage, the registration system, and the abstract

submission system of the conference.

Like always, our department staff Megan Petsa, Tracy Burke, and Hannah Melroy provided

tremendous, indispensable support, for which we are very grateful. This year, we used

the University Events and Conference Services, which turned out to be a pleasant experience. We

thank Kate Copeland and her team for their effort in coordinating the right resources at UConn

and taking care of the logistics for the conference.

The 32nd New England Statistics Symposium will be held on April 13–14, 2018, at the University

of Massachusetts, Amherst, MA.

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The Symposium local hosts and organizers from the University of Connecticut were Haim Bar (co-chair),

Jun Yan (chair), Yuping Zhang, and Kun Chen.

By Joseph Glaz

The ninth International Workshop in Applied Probability will take place at Eötvös Loránd

University, Budapest, Hungary, on June 18-21, 2018. IWAP is a biennial series of conferences

launched in 2002 with the aim of fostering exchange and cross-fertilization of ideas on applied

probability. It has been held in four continents, and returning to Europe, Budapest will host the

event in 2018. On behalf of IWAP International Board and Eötvös Loránd University, the organizers

invite you to attend the conference.

The 2018 Conference will provide opportunities for presentations on a wide range of theoretical

and applied topics, and recognizes the important role of probability and statistics in science and

society. The numerous scientific and social events—including the gala dinner served on a cruise

ship on the Danube—will present ample networking opportunities throughout the conference.

The Ninth International Workshop in Applied Probability

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Research presenters will be invited to submit for journal publication in a special issue of

Methodology and Computing in Applied Probability. With the scenic historic Budapest nearby, the

conference venue, the Lágymányos campus of Eötvös Loránd University is part of a recently built

innovation park, and provides modern facilities for all needs of the event. For more information

visit the workshop website at http://iwap2018.com.

Joseph Glaz ([email protected])

Deepak Agarwal Became an ASA Fellow in 2014.

Pantea Alirezazadeh Is an Analyst for 1010 Data.

Brien Aranov Is a Senior Consultant of Personal Insurance Research & Development at Travelers Insurance.

Brian Bader Joined KPMG LLP as a Statistician in Fall 2016.

Sudipto Banerjee Professor and Chair, Department of Biostatistics, University of California, Los Angeles and has been named Fellow of the Institute of Mathematical Statistics (IMS).

Swarnali Banerjee Became an Assistant Professor at Loyola University in Chicago in 2016.

Sudeep Bapat Is an Assistant Professor at the University of California, Santa Barbara.

Abhishek Bishoyi Completed his Ph.D. and accepted a research position at Selective Insurance, New Jersey.

Jennifer (Boyko) McGinniss Is an Associate Director of Biostatistics at Sunovion Pharmaceuticals and ASA CT Chapter President.

Wen Cao Completed her Ph.D. at Stern School of Business, NYU, and joined Credit Suisse.

65

Brad Carlin Chair of Biostatistics at the University of Minnesota and is still enjoying the job for the most part. He continues to focus primarily on methods for Bayesian adaptive clinical trials and network meta-analysis. He is also still leader of “the Bayesian band,” which has a new name and website: www.imposteriors.com.

Bhargab Chattopadhyay Made full-length invited paper presentation during the IWAP held in Jerusalem, Israel in June 2012 and chaired an invited paper session during the 4th IWSM hosted by the Department of Statistics at the University of Georgia-Athens in July 2013.

Saibal Chattopadhyay Professor, was appointed to the highly prestigious position of the Director at the Indian Institute of Management Calcutta in Calcutta, India, effective April 2013.

Ashok Chaurasia Has accepted a faculty position with the University of Waterloo, School of Public Health and Health Systems, Waterloo, Ontario, Canada

Steven Chiou Joined the Department of Mathematical Sciences, University of Texas at Dallas, as an Assistant Professor after a two year postdoc position with Harvard University’s Biostatistics Department.

Sourish Das Has become an Assistant Professor in the Mathematics Group at the Chennai Mathematical Institute, India. Currently, his research interest focuses on solving problems of Financial Mathematics and Applied Statistics via Bayesian methodology.

Ved Deshpande Received his Ph.D. in August 2017 and joined eBay (New York, NY) as a Research Engineer.

Ulysses Diva Is now working with AstraZeneca in Wilmington, DE as a Principal Statistician.

Gulsum Cinar Dolgun Is an Expert Assistant at TCMB.

Rongwei Fu was promoted to the rank of Full Professor at the Oregon Science and Health University, Portland, OR, and became an ASA Fellow in 2017.

Elijah Gaoioni Has joined New York Life Insurance Company as a Corporate Vice President, Data Science.

Miaomiao Ge Was recently promoted to Principal Biostatistician at Boehringer Ingelheim Pharmaceuticals, Inc.

Samiran Ghosh

66

Assumed the position of Director of Biostatistics at the Biostatistics and Epidemiology Research Design Core at Wayne State. Samiran also became an editor of PLOS-one and joined a NIH study section as reviewer.

Sujit Ghosh Was selected to serve as one of the Program Directors in the Division of Mathematical Sciences (DMS) within the National Science Foundation (NSF) beginning September 2013. Recently, he was offered the position of the Deputy Director of Statistical and Applied Mathematical Sciences Institute (SAMSI) beginning September 2014. He was elected to serve as the President of the NC Chapter of American Statistical Association (ASA) for year 2013. He was awarded the 2013 Thammasat University Honorary Plaque by the Government of Thailand. He has been given the 2013-2014 Cavell Bownie Mentoring Faculty Award by Department of Statistics at NC State University.

Gyuhyeong Goh Has joined Kansas State University as an Assistant Professor.

Feng Guo Has received his tenure with promotion to Associate Professor in the Department of Statistics, Virginia Tech, Blacksburg, Virginia.

Enida Halilovic Is an IT Project Analyst for United Health Care insurance company.

Patrick Harrington Is employed by Genomic Health Inc.

Yujing Jiang Started a postdoc position under the supervision of Dan Cooley of the Department of Statistics, Colorado State University, in Fall 2017.

Xun Jiang Has joined Amgen Biopharmaceutical Company in Thousand Oaks, CA as a biostatistician.

John (Anthony) Labarga Is an Advanced Analytics Intern at Travelers Insurance.

Chantal Larose Has accepted a position as Assistant Professor of Statistics at Eastern Connecticut State University, where she will join Dr. Marsha Davis, UConn Statistics alumna, who chairs the Math Department at ECSU. Chantal also recently published two research papers.

Wenqing Li Is a Director of Biostatistics and Data Management at Ventana Medical Systems, Inc. in Tucson, AZ.

Gong-Yi Liao Is employed by the Northern Trust Company.

Qi Liao Is a statistician at Merkle.

67

Dan Liu Received a letter for Teaching Excellence from the Provost and Vice Provost for Academic Affairs. Is a Statistician at Yale University Careers.

Junfeng Liu Is a consultant to GCE Solutions, Inc. in Bloomington, Illinois.

Ran Liu Joined Abbvie Pharmaceutical Research and Development, Chicago, as a Senior Biostatistician.

Xue Liu Has joined Towers Watson as an Actuarial Analyst.

Zhuping Liu Is pursuing a Ph.D. at the University of Texas-Austin in Marketing.

Chongliang Luo Completed his Ph.D. and accepted a postdoctoral position in the Division of Behavioral Sciences and Community Health, UConn Health.

Bani Mallick Was elected as an AAAS Fellow.

Madhuja Mallick Is an Associate Director at Forest Laboratories, Inc.

Gregory Matthews Won the 2016 SABR Contemporary Baseball Analysis Award and, together with his wife, Sarah, welcomed a baby girl, Amelia Ruth Matthews in September 2016.

Athanasios Christou Micheas Athanasios Micheas, Associate Professor, University of Missouri, Columbia, serves as an Associate Editor for the Journal of Statistical Computation and Simulation. His first textbook, Theory of Stochastic Objects: Probability, Stochastic Processes and Inference, is currently in production and is expected to appear in January 2018. He is also completing a second textbook, Theory and Modeling of Stochastic Objects: Point Processes and Random Sets, which is expected to be published in the Fall of 2018.

Aditya Mishra Completed his Ph.D. and received a Simons Foundation fellowship. He will be employed at the Foundation’s Flatiron Institute, New York, NY.

Jaydip Mukhopadhyay Is the director of Model Risk and Governance at American Express in Gurgaon, India.

Stephen O’Malley Is an Analytics Manager at Health Dialog.

Guang Ouyang Joined the Google Mountain View office as a member of the Display and Video Ads team.

68

Valerie Pare Is a Professor of Practice at Wesleyan University.

Sankha Muthu Poruthotage Has joined Plymouth Insurance, Boston, MA, effective September 1, 2013.

Sairam Rayaprolu Has joined Disney as a Decision Science Consultant in Orlando, FL.

Dooti Roy Completed her Ph.D. and is working at Boerhinger-Ingelheim Pharmaceutical Company in Ridgefield, CT as a Senior Biostatistician.

Abhishek Saha Is a Senior Consultant at Cognizant.

Hongwei Shang Joined Yahoo Research as a Research Scientist in 2016.

Daoyuan Shi Completed his Ph.D. in August 2017 and has joined Vertex Pharmaceuticals.

Wei Shi Completed his Ph.D. in December 2016 and works at Mapfre Insurance.

Tumulesh K. S. Solanky Professor and Head, made a full-length invited paper presentation and chaired an invited paper session during the 4th IWSM hosted by the Department of Statistics at the University of Georgia-Athens, July 2013.

Elizabeth Tripp Is pursuing a Ph.D. in the Math Department at Dartmouth College, New Hampshire and a member of the Epsilon of Connecticut Chapter of Phi Beta Kappa in recognition of her superlative undergraduate academic achievements.

Gregory Vaughan Joined the Department of Mathematical Science, Bentley University, as an Assistant Professor for Fall 2017.

Chun Wang Is a Senior Analyst at Liberty Mutual Insurance and helped fundraise for the Liberty Mutual Poster Awards at the 31st New England Statistics Symposium in April 2017.

Leo Wang Has joined Millennium Management Investment Company in New York City as a fixed income trader

Xia Wang Received promotion and tenure as Associate Professor at the University of Cincinnati, Ohio.

Xiaojing Wang At Google, Inc.

69

Yu-Bo Wang Is a Post-Doctorate Fellow at the National Institute of Child Health and Human Development (NICHD/NIH).

Yue Wang Is working for Aetna Insurance Company as an Analyst.

Zhuo Wang Became an Assistant Professor in the Department of Economic Statistics, Shenzhen University, China, in 2016.

Ziwen Wei Is employed at Merck & Co., Inc.

Jing Wu Received her Ph.D. in August 2017 and joined the University of Rhode Island, Department of Computer Science and Statistics, in Kingston, RI as an Assistant Professor.

Qianzhu Wu Completed her Ph.D. in August 2016 and joined Liberty Mutual Insurance Co.

Rui Wu Is employed at Novartis Oncology.

Hui Yao Is a Senior Predictive Modeler at Ernst & Young.

Jieyang Zang Is a Customer Data Analyst at Symphony EYC.

Danjie Zhang Is a Biostatistician II at Gilead Sciences, Inc.

Yaohua Zhang Completed his Ph.D. in August 2017 and has joined Vertex Pharmaceuticals.

Bo Zhao Joined the Liberty Mutual Group, Inc. in Boston, MA.

70

Graduate Student Committee 2017-2018 Left to right: Yuan Zhang (Member), Disheng Mao (Secretary), Yang Liu (President), Qingyang Liu

(Member), Yixin Xiang (Member), Jieying Jiao (Senator), Wei Shi (Treasurer), Yishu Xue (Vice President), Xiaokang Liu (Senator), Prince Allotey (Member) Members not pictured – Renjie Chen, Xiuyuan Liu

The Graduate Student Committee is dedicated to serving the graduate students and

working closely with the department’s faculty members to organize social and academic

events. This year, the Committee has successfully organized two “pizza nights,” which

helped newly joined students get familiar with each other. Many members from the

Committee also served as volunteers in several academic conferences held by the

department, like NESS. The Committee also helps organize the annual department picnic.

The Committee is grateful for the generous support from the department and will continue

to provide excellent service to the graduate students.

Officers Members

Yang Liu, President Prince Allotey

Yishu Xue, Vice President Renjie Chen

Wei Shi, Treasurer Qingyang Liu

Disheng Mao, Secretary Xiuyuan Liu

Jieying Jiao, GSS Senator Yixin Xiang

Xiaokang Liu, GSS Senator Yuan Zhang

71

Phi Beta Kappa Inductees The following undergraduate Statistics majors were elected to Phi Beta Kappa, the nation’s oldest and most widely recognized honors society celebrating achievement in the liberal arts and sciences in 2017: Francisco Tomas Cifuentes Villarroel Sarah Cynthia Crothers Jessica Hope Lerner Samuel Schick Emily Elizabeth Stiles

Lijiang Geng (Advisor M.-H. Chen) Best Performance in Probability, AY 2016-2017

Yeongjin Gwon (Advisor M.-H. Chen) Department of Statistics Service Award, AY 2016-2017

Jieying Jiao (Advisor M.-H. Chen) Gottfried Noether Award for Mathematical Statistics, AY 2016-2017

Hao Li (Advisor M.-H. Chen) Department of Statistics Service Award, AY 2016-2017

Matthew Linder (Advisor Zhang) Completed a summer internship at Apple.

Yan Li (Advisor Yan) Gottfried Noether Award for Mathematical Statistics, AY 2016-2017 Mark of Excellence Award for Stellar Performance in the Ph.D. Qualifying Exam, AY 2016-2017

Qingyang Liu (Advisor M.-H. Chen) H. Fairfield Smith and Dolores S. Smith Award for Excellence in Applied Statistics, AY 2016-2017 Mark of Excellence Award for Stellar Performance in the Ph.D. Qualifying Exam, AY 2016-2017

Yang Liu (Advisors M.-H. Chen, X. Wang) Won an ACTNext Travel Award to attend and present at the 2017 International Meeting of the Psychometric Society in Zurich, Switzerland. Best Performance in Inference, AY 2016-2017

Disheng Mao (Advisor Zhang) Received travel awards for the 24th Quality and Productivity Research Conference and Summer Institutes at the University of Washington.

Qian Meng (Advisor Glaz)

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Completed a summer internship at the Biostatistics and Computational Biology Branch, NIEHS, Research Triangle Park, NC

Yulia Sidi (Advisor Harel) H. Fairfield Smith and Dolores S. Smith Award for Excellence in Applied Statistics, AY 2016-2017

Gregory Vaughn (Advisor K. Chen, Yan) Won the Student Paper Award from the Mental Health Section of the American Statistical Association in 2017.

Wenjie Wang (Advisors Yan, K. Chen) Won a IBM Student Paper Award at the 31st New England Statistics Symposium, 2017 Department of Statistics Service Award, AY 2016-2017

Cheng Zhang (Advisor M.-H. Chen) Mark of Excellence Award for Stellar Performance in the Ph.D. Qualifying Exam, AY 2016-2017

Recent Bachelor’s

Francis Amechi Abadom, Patrick Augustine Adams, Marzouk Adoyi, Danielle Marie Albino,

Joseph Robert Bernard, Matthew Aaron Blais, Avery Connor Boissy, Bethany Antoinette Brown,

Bryan Cheng, Jae Seong Cho,Rick Cooper, Hannah Rose David, Craig Richard Davis, Dena

Dhanraj, Jiawen Du, Surath Isuru Fernando, Jazmin Foy, Alexander Pierce Gulakos, Yizhuo Han,

Hakema Hussein Hussein, Nicholas Andrew Illenberger, Zachary Emerson Jacobs, Zhengyang

Kang, Alexander Karl, Yuan Ke, Jung Won Kim, Yuen Tsz Abby Lau, Allison Marie Leather, Janet

Lee, Jessica Hope Lerner, Xinyi Liu, Hanwen Liu, Xinyang Liu, Evelyn Marie Luchs, Jared Tyler

Lynch, Alexander Mark Mitteness, Bailey Mulqueen, Jennifer Park, Naga SriLekha Perumalla,

Manali Avinash Phadke, Carolyn Ann Polomsky, Clare Elizabeth Quinn, James Ray Jr, Samuel

Schick, James Christian Schirber, Morgan Rae Schuler, Kristen Shevlin, Joseph Daniel Shrager, Ari

Jaredd Solomon, Emily Elizabeth Stiles, Joseph Robert Tomastik, Cindy Tran, Lucas David

VanhausenAni Wang, Wuyan Xu, Zhangtongxin Yang, Yuhao Yao,

73

Recent Master’s

Shaochen Bai, Ved Deshpande, Kelly Duda, Hao Chen, Yuliang Chen, Jialin Han, Zheyu Jiang, John

Anthony Labarga, Yi Le, Chaoyu Lin, Muye Lin, Dan Liu, Qinqing Liu, Chongliang Luo, Aditya

Kumar Mishra, Dooti Roy, Fei Sha, Xiaoyan Tang, Jing Wu, Bing Yan, Kewei Yan, Kaicun Yuan,

Shanglin Zhou, Yichen Zhou, Xiwen Zhu, Zimin Zhuang, Ruochen Zha

Recent Ph.D.’s

Sudeep Bapat, Abhishek Bishoyi, Ved Deshpande, Wei Fu, Yujing Jiang, Chongliang Luo, Aditya

Kumar Mishra, Dooti Roy, Daoyuan Shi, Jing Wu, Gregory Vaughan, Yaohua Zhang

UConn Statistics Alumni:

We would love an update on your current activities. Please send updates (professional and/or

personal) to [email protected] to be included in the next issue of the newsletter. Please be

sure to include the year you graduated and the degree received in your email.

Interested in supporting the department? We welcome alumni donations, which may be used for

graduate fellowships, travel awards that allows faculty and students to present their research at

conferences, and for special events such as seminars and lectures. Please contact us for more

information on how you can support the Department of Statistics.

Thank you and we look forward to hearing from you!

The Department of Statistics

Robert Apruzese, Adjunct Lecturer [email protected]

Robert Aseltine, UConn Health Joint Appointment [email protected]

Haim Bar, Assistant Professor [email protected]

Tracy Burke, Secretary [email protected]

Attention, Alumni! We want to hear from you!

Department Directory

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Joseph Cappelleri, Adjunct Professor (Pfizer, Inc.) [email protected]

Kun Chen, Assistant Professor [email protected]

Ming-Hui Chen, Professor and Head [email protected]

Zhiyi Chi, Professor and Associate Head [email protected]

Victor Hugo Lachos Davila, Professor [email protected]

Dipak K. Dey, Distinguished Professor [email protected]

Joseph Glaz, Professor [email protected]

Yuwen Gu, Assistant Professor [email protected]

Ofer Harel, Professor [email protected]

Kent Holsinger, EEB Joint Appointment [email protected]

Tania Huedo-Medina, Allied Health Joint Appointment [email protected]

Lynn Kuo, Professor [email protected]

Paul Lewis, EEB Joint Appointment [email protected]

Néhémy Lim, Visiting Assistant Professor [email protected]

Suman Majumdar, Associate Professor (Stamford) [email protected]

Kathleen McLaughlin, Adjunct Lecturer [email protected]

Nitis Mukhopadhyay, Professor [email protected]

Megan Petsa, Program Assistant [email protected]

Vladimir Pozdnyakov, Professor and Director of Financial Math [email protected]

Zhanna Pozdnyakova, Adjunct Lecturer [email protected]

Nalini Ravishanker, Professor [email protected]

Elizabeth Schifano, Assistant Professor [email protected]

Naitee Ting, Adjunct Professor (Boehringer-Ingelheim) [email protected]

Emiliano Valdez, Math Joint Appointment [email protected]

Richard Vitale, Professor [email protected]

Stephen Walsh, School of Nursing Joint Appointment [email protected]

HaiYing Wang, Assistant Professor [email protected]

Xiaojing Wang, Assistant Professor [email protected]

Michael Willig, CESE Joint Appointment [email protected]

Jun Yan, Professor [email protected]

Panpan Zhang, Visiting Assistant Professor [email protected]

Yuping Zhang, Assistant Professor [email protected]

the department of statistics - university of connecticut · i would like to welcome victor hugo...

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