2023 Elected Officials Profiles
President
Daniel H. Silberberg Professor of Statistics and Data Science, The Wharton School
Professor, Applied Mathematics and Computational Science Graduate Group
Associate Scholar, Department of Biostatistics, Epidemiology, and Bioinformatics, Perelman School of Medicine
Department of Statistics and Data Science
University of Pennsylvania
Education
- B.S. Mathematics, 1986, Hangzhou University, China
- M.S. Applied Mathematics, 1989, Shanghai Jiao Tong University, China
- M.A. Mathematics, 1992, State University of New York at Buffalo, USA
- Ph.D. Statistics, 1996, Cornell University, USA
Research Interests
- Statistical machine learning
- High-dimensional statistics
- Large-scale inference
- Statistical decision theory
- Functional data analysis
- Nonparametric function estimation
- Applications to genomics and financial engineering
Previous Service to the Profession
- Co-Editor, Annals of Statistics, 2010-12
- Associate Editor, JRSSB (2014-18), JASA(2005-2010), Annals of Statistics (2004-09), Statistica Sinica (2005-11), Statistics Surveys (2006-09)
- Board of Advisors, Institute for Mathematical and Statistical Innovation, 2020-2024
- IMS Council (2020-23)
- COPSS Distinguished Achievement Award & Lecture Committee, 2020-23
- Program Co-Chair, IMS Annual Meeting 2017 and 2007
- Bernoulli Society Publications Committee, 2011-14
- COPSS Presidents’ Award Committee, 2009-12, 2014; Chair, 2012
- IMS Committee on Special Lectures 2008-12
- IMS Committee on Nominations 2008-09
- Co-Chair, Scientific Committee, IMS-China International Conference, Weihai, China, 2009
- IMS Committee to Select Editors 2000-03
Brief Statement
It is an honor to be nominated for the IMS Presidency. The importance of statistics and data science cannot be overstated in today’s data-driven world. As a leading scholarly society in statistics, IMS plays a crucial role in advancing the discipline through its numerous initiatives and activities. My vision is to continue the outreach efforts to industry and diverse geographic regions, expand the membership base to foster a more inclusive and collaborative community, enhance fundraising efforts to support new researchers, and expand the activities in data science and other areas related to data-driven AI.
Council
You may view the profile for each council member by clicking on their name below.
Professor of Mathematics and Statistics, Department of Mathematics and Department of Statistics, Stanford University
Education
- Bachelor of Statistics, 2000, Indian Statistical Institute, Kolkata, India
- Master of Statistics, 2002, Indian Statistical Institute, Kolkata, India
- Ph.D. in Statistics, 2005, Stanford University, USA
Research Interests
- Probability theory
- Mathematical statistics
- Mathematical physics
Previous Service to the Profession
- Member of the Scientific Research Board of the American Institute of Mathematics, 2022 – 2025
- Member of the Scientific Advisory Committee of the Simons Laufer Mathematical Sciences Institute (formerly Mathematical Sciences Research Institute), 2022 – 2026
- Associate editor for the Proceedings of the London Mathematical Society, 2023 onwards
- Associate editor for the Annals of Applied Probability, 2022 onwards
- Associate editor for Communications in Mathematical Physics, 2019 onwards
- Associate editor for Sankhya, Series A, 2012 – 2015
- Associate editor for Probability Theory and Related Fields, 2011 – 2015
- Associate editor for the Annals of Probability, 2009 – 2014
- Associate editor for the Annales de l’Institut Henri Poincare (B), 2008 – 2013
- Organized many conferences and workshops and served on IMS committees
Brief Statement
It is a great privilege and honor to be nominated for election to the IMS council. The IMS plays a very important role in supporting mathematical statistics and probability throughout the world, and I will do my best to help advance its causes. I am particularly interested in maintaining the high quality of the IMS journals, and promoting IMS initiatives for increasing diversity and outreach to underrepresented communities.
ICREA Research Professor, Department of Economics and Business, Pompeu Fabra University, Barcelona, Spain
Education
- Ph.D. in Electrical Engineering, 1991, Hungarian Academy of Sciences, Hungary
- M.S. in Electrical Engineering, 1987, Technical University of Budapest, Hungary
Research Interests
- Theory of machine learning
- Combinatorial statistics
- Inequalities in probability
- Random graphs and random structures
- Information theory
Previous Service to the Profession
- Editor and co-founder of Mathematical Statistics and Learning (2017–)
- Associate editor of Annals of Applied Probability (2016–2021)
- Associate editor of Probability Theory and Related Fields (2015–)
- Action editor of Journal of Machine Learning Research (2005–)
- Member of the editorial board of Machine Learning Journal (2006–2020)
- Associate editor of TEST (2002–)
- Associate editor of ESAIM: Probability and Statistics (2005–)
- Associate editor of IEEE Transactions on Information Theory (1999–2002)
- Associate editor of Statistics & Decisions (2002–2011)
- Associate editor of Scandinavian Journal of Statistics (2010–2015)
- Member of the editorial board of Foundations and Trends in Machine Learning (2007–)
Brief Statement
It is a great honor to be nominated to the IMS Council. Both probability and
statistics are booming largely thanks to the new challenges coming from
data science, machine learning, bioinformatics, and other fields. IMS faces
the challenge of keeping a leading role in this increasingly competitive
environment and promoting rigorous thinking. I would be honored to help
maintain this leadership.
Full Professor at MIT, and Co-Director of the Eric and Wendy Schmidt Center at the Broad Institute, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology (MIT) and Broad Institute
Education
- PhD in Statistics, 2011, UC Berkeley
Research Interests
- Causal inference
- Probabilistic graphical models
- Representation learning and generative modeling
- Applications to genomics
Previous Service to the Profession
- IMS representative, Joint Committee on Women in the Mathematical Sciences (2017-2020)
- Council Member (elected), International Statistical Institute (2021-2025)
- Elected member, Scientific Advisory Board of the Gladstone Institutes (2023)
- General and Program Chair of inaugural CLeaR Conference (2022)
- Advisor, Science Advisory Board, Chan Zuckerberg Initiative (2022)
- Judge for the Regeneron Science Talent Search (2015-2021)
- International Conference on Machine Learning (ICML) tutorial co-chair, (2021)
- International Conference on Machine Learning (ICML) sponsorship co-chair (2020)
- Damon Runyon Quantitative Biology Fellowship Award Selection Committee (2020-present)
- Associate editor, SIAM Journal on Mathematics of Data Science (2020-2022)
- Associate editor, SIAM Journal on Applied Algebra and Geometry (2019-2022)
- Associate editor, Harvard Data Science Review (2019-2022)
- Program Director, SIAM Activity Group on Algebraic Geometry (2018-2020)
Brief Statement
Given the data explosion that we are witnessing in many fields, the combination of statistics and computation is becoming ever more critical. Building on my experience working at the intersection of mathematical statistics, machine learning, and genomics, I would be excited to contribute towards strengthening the links between the IMS and the broader data science community. The IMS plays a critical role in developing and nurturing the current and next generation of mathematical statisticians world-wide. I would be truly honored to serve as an IMS council member and promote a diverse and inclusive community.
Education
- Ph.D. (Statistics), 2006, University of Illinois, Urbana-Champaign, IL, USA
- M.S. (Statistics), 2002, Fudan University, Shanghai, China
- B.S. (Statistics), 1999, Fudan University, Shanghai, China
Research Interests
- Extreme value theory and applications
- Bioinformatics and biostatistics
- Longitudinal data analysis
- Nonparametric (semiparametric) regression
- Quantile Regression
- Spatial data analysis
- Survival analysis
Previous Service to the Profession
- Service to IMS:
- IMS Program Chair for 2023 Joint Statistical Meetings, 2022-2023 (Chair)
- Joint Bernoulli Society/IMS Publications Management Committee, 2021-2024 (Member)
- IMS Committee on Nominations, 2018-2019, 2020-2021 (Member)
- Editorial services:
- Associate Editor for The Annals of Statistics (2013 – Present)
- Associate Editor for the Journal of the American Statistical Association (Theory and Methods), 2011-Present
- Associate Editor for Bernoulli, 2022-Present
- Associate Editor for Stat, 2015-2021
- Associate Editor for the Review Sections of the Journal of the American Statistical Association and The American Statistician, 2013-2016
- Other professional services:
- Program Director, Division of Mathematical Sciences, US National Science Foundation, 2018-2022
- Committee of Presidents of Statistical Societies (COPSS), 2019-2021 (Secretary and Treasurer)
- International Chinese Statistical Association (ICSA), Program Committee for ICSA Applied Statistics Symposium, 2021 (Co-Chair)
- ICSA, Award Committee, 2018-2020 (Member), 2020-2021 (Chair)
- ICSA, Award Committee, 2018-2020 (Member), 2020-2021 (Chair)
- International Indian Statistical Association (IISA), Student Paper Competition Committee for IISA International Conference on Statistics, 2017 (Member)
- ASA, Section on Nonparametric Statistics, 2014 (Secretary), 2015 (Treasurer)
- ASA, Section on Nonparametric Statistics, Student Paper Competition Committee, 2015 (Member)
- Eastern North American Region (ENAR), Organizing Committee for Junior Researcher’s Workshop, 2012 (Member)
- ICSA, Program Committee, 2012 (Member)
- International Conference of Robust Statistics (ICORS), Organizing Committee, 2012 (Member)
- ENAR, Program Committee for ENAR Spring Meeting, 2011 (Member)
- ASA, Local Organizing Committee, Women in Statistics Conference, 2014 (Member)
- ICSA, Program Chair for 2011 JSM, 2011
- ASA, General Methodology Program Chair for 2010 JSM, 2010
Brief Statement
I am honored and humbled to be nominated for the IMS Council. Serving on editorial boards and publication, program, and awards committees has been an incredibly rewarding experience. I am excited to have the opportunity to continue contributing to the IMS community by upholding the high standards of the IMS journals, promoting diversity, supporting the next generation of researchers, and fostering interdisciplinary collaboration between probability, statistics, and other fields. With the rapidly changing landscape of data science and statistics, IMS plays a critical role in advancing the field. I am eager to contribute to its mission of supporting the community and creating broader impacts.
Professor of Statistics and Data Science, Department of Statistics and Data Science, The Wharton School, University of Pennsylvania
Education
- PhD, 1993 from Cornell University
Research Interests
- Network data
- Data driven decisions in Business
- Crowd sourcing
- Post model selection inference
- Methods in model free settings
- Non-parametric empirical Bayes
Previous Service to the Profession
- IMS fellow committee, 2021 –
- ASA Noether Awards Committee, 2021-
- Fundraiser and the committee (2019) launching IMS Lawrence D. Brown Ph.D. Student Award
- CWS (Caucus for Women in Statistics), IMS Liasson, Chair of Public Relations Committee, 2016 –
- Co-organizers of WiDS@Penn conference, 2021 – (Women in Data Science)
- Organizer of DSL, 2019 – (Data Science Live workshop at Penn)
- ICSA various committees
- ENAR 2013 IMS Program Chair, Orlando
- Former Associate editors for JSPI, Statistica Sinica and Journal of Asia Business Studies
Brief Statement
As a proud lifetime member of IMS, I am deeply honored to be nominated for the IMS council. In the new era of data science, I strongly believe that IMS should lead the way in solving data problems in science, social science, medicine, business, and government, while providing fundamental theoretical foundations for data science. I would like to continue to contribute to strengthening and broadening IMS’s role in 1) bridging statistics, data science, and related fields, and fostering interdisciplinary research, 2) creating more career development opportunities, especially for students, as well as young, women, and underrepresented researchers, and 3) developing modern statistics and data science pedagogies for the changing landscape of our field.