2019 Nominees

President-Elect Nominee

Regina Y. Liu

Distinguished Professor, Department of Statistics, Rutgers, the State University of New Jersey, USA

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Education

  • PhD and M. Phil, Statistics, Columbia University (1983)
  • BS, Applied Mathematics, Soochow University, Taiwan (1975)

Research Interests

  • Fusion learning
  • Confidence distribution
  • Data depth
  • Nonparametric and robust inference
  • Resampling
  • Aviation safety and risk management

Previous Service to the Profession

  • IMS Nominating Committee, Chair /Member, 1992-1993; 2004-2005, 2015-2017
  • IMS Committee of Editors, 2015-2017
  • Committee on Fellows, 2011-2014
  • Program Chair, IMS Program, Vancouver, 2010
  • IMS Special Lectures Committee, Chair/Member, 2005-2008
  • Associate Editor, The Annals of Statistics, 2000-2004
  • IMS Council, Member, 1999-2002
  • Program Chair, IMS Annual Meeting, Boston, 1992

Brief Statement

The IMS is the foremost society in statistics and probability worldwide, and I am deeply honored to be nominated as its President-Elect.  Recent years have witnessed a phenomenal expansion of statistics and probability in all directions of data science. With this success come also many challenges and opportunities, which I hope to address if elected. In its broadest sense, data science interacts with many fields in both science and the humanities, and data science researchers can be widely dispersed in academia, high tech and financial industries, or government agencies. The IMS is ideally positioned to provide a common core and a welcoming home for all, including an effective platform for interactions and dissemination of important advances. Simultaneously, a goal of the IMS should be to raise the profile of the field and to ensure an influx of fresh talent to keep it vibrant and dynamic.


Council Nominees

Ming-Yen Cheng

Professor, Department of Mathematics, Hong Kong Baptist University

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Education

  • PhD in Statistics, 1994, University of North Carolina at Chapel Hill

Research Interests

  • Classification and clustering
  • Change-points
  • High-dimensional data
  • Nonparametric and semiparametric models

Previous Service to the Profession

  • Member, Award Committee, ICSA, 2016-2017
  • Member, Ad Hoc Committee on Peter Hall Award, 2016
  • Member, Organizing Committee for the International Prize in Statistics, ASA, 2016
  • Member, Board of Directors, ASA, 2014-2016
  • Member, Committee on Nominations, IMS, 2007-2008, 2014-2015
  • Member, Committee on Fellows, IMS, 2009-2011
  • Member, Committee on Asia Pacific Rim Meetings, IMS, 2007-2009, 2012-2014
  • Member, Nomination and Election Committee, ICSA, 2009-2010
  • Associate Editor, Annals of Statistics (2004-2009, 2016-2018), Journal of the American Statistical Association (2011–), The American Statistician (2017–), Statistica Sinica (2002-2014), Lifetime Data Analysis (2005–), Journal of the Korean Statistical Society 2008-2016), etc.

Brief Statement

I am extremely honored to be nominated for the IMS Council election. The IMS has long been playing a central role in advancing the development of probability and statistics and the fostering of new generations. In the era of data science, our profession face excitements as well as challenges in the efforts to be inclusive and visible and to lead. If elected, I would contribute towards these efforts.


Haiyan Huang

Professor, Department of Statistics, Graduate Group in Biostatistics, Center for Computational Biology

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Education

  • BS, Mathematics, 1997, Peking University, China
  • PhD, Applied Mathematics, 2001, University of Southern California, USA

Research Interests

  • Statistical genomics
  • Bivariate dependence modeling
  • Biological network inference
  • Translating genomics features into therapeutics

Previous Service to the Profession

  • 2004-2015: Associate Editor, Statistical Applications in Genetics and Molecular Biology
  • 2005: Organization Committee Member, IMS/CSPS joint meeting in Beijing, PR China, 2005
  • 2009: IMS Program Chair, 2009 WNAR/IMS annual meeting
  • 2014-2015: Serving on a National Research Council committee
  • 2014-present: Editorial Board Member, Journal of Computational Biology
  • 2015-2016: Member, Nomination Committee, Institute of Mathematical Statistics (IMS)
  • 2015-present: Associate Editor, Annals of Applied Statistics (AOAS)
  • 2016-present: VP of Scientific Outreach and co-founder, DahShu (http://www.dahshu.org/, a non-profit organization to promote research and education in data sciences)
  • 2017-present: Associate Editor, Journal of the American Statistical Association (JASA), Theory & Methods

Brief Statement

It is an honor to be nominated for the IMS council, and it will be my privilege to serve. I have long observed the dedication of IMS colleagues, from near and afar, in strengthening our international community.  I deeply appreciate the support this community has given me during my career. If elected, I will initiate new efforts to support young professionals, from diverse backgrounds, to promote their careers.  I will also work to enhance the impact of mathematical statistics on science and society. Building on my interdisciplinary background, I will help connect IMS with other disciplines to expand the opportunities for our members to broaden their careers.


Mia Hubert

Professor, Department of Mathematics, University of Leuven, Belgium

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Education

  • 1992 – M. Sc. in Mathematics, University of Antwerp, Belgium
  • 1997 – Ph.D. in Science (Statistics), University of Antwerp, Belgium

Research Interests

  • Robust statistics
  • Outlier detection
  • Depth functions
  • Statistical process control
  • Development of statistical software

Previous Service to the Profession

  • 2001-2005: Associate editor for Journal of Computational and Graphical Statistics
  • 2007-2011: Associate editor for Computational Statistics and Data Analysis
  • 2008-2017: Associate editor for Technometrics
  • 2008-2018: member of the Editorial Board of Journal of Chemometrics
  • 2019- : Associate editor for Statistical Methods and Applications
  • Elected member, Board of Directors of the European Regional Section (ERS) of the International Association for Statistical Computing (IASC)
  • Elected member of ISI; member of ASA, IASC, IMS

Brief Statement

If elected, I would like to strengthen the interplay between theoretical mathematical statistics/probability and applied statistics. Nowadays, with the unlimited availability of new data types (such as internet and social network data), we are facing many new problems. I would like the IMS to create opportunities for both theoretical and applied statisticians to tackle these challenges, and to learn from each other. As such, we might reinforce our important role within Data Science.


Edwin Perkins

Canada Research Chair in Probability, Department of Mathematics, University of British Columbia, Canada

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Education

  • U. of Toronto, B.Sc., 1975
  • U. of Illinois at Urbana-Champaign, Ph.D., 1979

Research Interests

  • Branching models, measure-valued processes and connections with population genetics and mathematical ecology
  • Stochastic pde
  • Interacting particle systems
  • Stochastic differential equations, Brownian motion and stochastic analysis

Previous Service to the Profession

  • Board of Directors of the Pacific Institute for Mathematical Sciences (1996-2017)
  • Vice-President, Canadian Mathematical Society, 2005-07
  • Committee for Conferences on Stochastic Processes, Bernoulli Society
  • IMS Nomination Committee (two terms)
  • Scientific Panel, Seminar on Stochastic Processes
  • Editorial Boards:
    • Annals of Probability (2012-17)
    • Annals of Applied Probability (1997-99)
    • Probability Theory and Related Fields (1983-1994)
    • Electronic J. Probability and Electronic. Comm. Probability (2002-2011)
    • Ann. Inst. Henri Poincar´e (1994-2016)
    • Can. J. Math. (1994-99)

Brief Statement

I believe that statistics and probability have more to offer each other than many realize, and that continued involvement of both disciplines in the IMS, is one of its strengths. If elected, I will work hard on supporting the laudable, but at times conflicting, goals of building an open access and relevant publication system on one hand, and maintaining a fiscally healthy IMS on the other.


Gesine Reinert

Professor, Department of Statistics, University of Oxford

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Education

  • Diploma, Mathematics, 1989, University of Goettingen
  • PhD, Applied Mathematics, 1994, University of Zürich

Research Interests

  • Probabilistic approximations, in particular Stein’s method
  • Analysis of networks
  • Biological sequence analysis

Previous Service to the Profession

  • Since January 1, 2019: Chair of the Royal Statistical Society Applied Probability Panel
  • Since January 1, 2019: Associate Editor, Bernoulli 
  • Since 2017: IMS journal panel
  • 2017 – 2018: Secretary of the Royal Statistical Society Applied Probability Panel
  • Since 2017: Associate Editor, Journal of Computational Biology
  • Since 2016: Vice-Chair, European Cooperation for Statistics of Network Data Science
  • 2012 – 2018: Associate Editor, Journal of Applied Probability
  • 2012-2017: IMS Nomination Panel
  • 2005-2010: Associate Editor, Bernoulli 

Brief Statement

It would be a great honour to serve on the IMS Council. The IMS is an outstanding professional organisation which embraces change while being rooted in solid scientific foundations.  The area of statistics often develops in a dynamic interplay with application areas and new technological possibilities. To explore such areas, both junior researchers and experienced statisticians are needed. The inclusive approach of the IMS fosters such activities across disciplines and career stages, and it would be a privilege to contribute to this endeavour.


Markus Reiß

Professor, Institute of Mathematics, Humboldt-Universität zu Berlin

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Education

  • Diploma in Mathematics, Free University Berlin, 1999
  • Ph.D., Humboldt University Berlin, 2002

Research Interests

  • Nonparametric and High-dimensional Statistics
  • Statistics for Stochastic Processes and SDEs
  • Statistical Inverse Problems

Previous Service to the Profession

  • Editor-in-Chief for Bernoulli 2019-2022, for Statistics, 2012-2015
  • AE for Annals of Statistics 2008-2018, Stoch. Processes Appl. 2009-2018, Statistics 2010-2012
  • Organizer of several larger meetings in statistics, e.g. this year Statistical and Computational Aspects of Learning with Complex Structure in Oberwolfach

Brief Statement

Knowing also a bit the scientific communities in neighbouring disciplines, e.g. in pure math or numerical analysis, I am more than happy to work in mathematical statistics. I believe that our community unites highest scientific standards with respectful and congenial cooperation. The part that the IMS contributes to this cannot be underestimated and I want to strongly support it further. I am particularly willing to invest myself in the excellent publication series and journals and in the European participation at IMS activities.


Christian Robert

Professor, Department of Mathematics & Department of Statistics, Universie Paris Dauphine & University of Warwick

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Education

  • PhD (Rouen, France) 1987

Research Interests

  • Bayesian statistics, from foundations to methodology to applications
  • Computational statistics (Monte Carlo methods, MCMC, ABC)

Previous Service to the Profession

  • Member of several IMS committees over the years
  • AE for Annals of Statistics for 13 years

Brief Statement

I am most interested in keeping and promoting the IMS as a diverse and top scientific society representative of all academics in probability, statistics, machine learning, ensuring both preserving the same highest academic standards as throughout its history and leading the data science revolution. This means pursuing novel ways of publishing and assessing research, providing tribunes and support to junior researchers, and guaranteeing an inclusive approach to research and dissemination.


Chiara Sabatti

Professor, Biomedical Data Science and Statistics, Stanford University

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Education

  • BS in Economic and Social Disciplines, 1993, Bocconi University
  • Ph.D in Statistics, 1998, Stanford University

Research Interests

  • Statistical genomics
  • Model selection
  • Adjustments for multiplicity and selection
  • Relation between Bayesian and frequentists methods in high dimensional data analysis

Previous Service to the Profession

  • Associate editor for Genetics (2012-present), JASA (2011-15), The Annals of Applied Statistics (2010-present), BMC Bioinformatics (2010-present), IEEE/ACM Transaction on computational Biology and Bioinformatics (2004-10)
  • Grant review panel member for NSF and NIH
  • Organizers of IPAM workshops “Sequence analysis towards system Biology” (2006) and “Computational genetics” (2007) and sessions at ASHG 2005, Interface 2006, and JSM 2011

Brief Statement

Our profession enjoys a renewed popularity and the IMS has an important role to play in this landscape. It should continue to foster the advancement of our discipline, capitalizing also on the vitality of other research domains as optimization and computer science, etc. We have the  opportunity to reaffirm and enable sound scientific methods, developing approaches that facilitate reproducibility and replicability of scientific results. And we need to reach out to the public at large, making sure that society has a “healthy” relationship with data: not assuming that “its speak for itself” nor developing an indiscriminate and disabling skepticisms. To achieve these goals I believe it is crucial (1) to revisit creatively foundational questions; (2) to  engage in long term collaborations with domain specialists working with an unprecedented wealth of data; (3) to  enlarge the scope of our educational efforts.  IMS has also the opportunity to foster a diverse and inclusive environment, that cultivates and benefits from the unique perspectives of individuals of different genders, ethnic and cultural backgrounds.


Qi-Man Shao

Chair Professor, Department of Statistics and Data Science, The Southern University of Science and Technology, China

Choh-Ming Li Professor of Statistics, Department of Statistics, The Chinese University of Hong Kong, Hong Kong, SAR

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Education

  • B.S., Mathematics (1983), Hangzhou University, China
  • Ph.D, Probability and Statisitcs (1989), University of Science and Technology of China

Research Interests

  • Asymptotic theory in probability and statistics
  • Self-normalized limit theory
  • Stein’s method for normal and non-normal approximation
  • High-dimensional and large scale statistical analysis

Previous Service to the Profession

  • Associate editor, The Annals of Statistics (2003-2012)
  • Associate editor, The Annals of Applied Probability (2006-2012)
  • Associate editor, Bernoulli (2013- present)
  • IMS Committee on Fellows, Member (2007-2009, 2011), Chair (2009)
  • Member, IMS Committee on Nominations (2011, 2016, 2017)
  • Chairman, Local organizing committee, the 4th IMS Asian Pacific Rim Meeting, 2016
  • Co-chair, Scientific Program Committee, the 5th IMS Asian Pacific Rim Meeting, 2018

Brief Statement

My main area of research is in asymptotic theory in probability and statistics. In Big Data era, data have become the world’s most valuable resource. IMS can play a leading role in accelerating scientific discovery and innovation in data science, promoting basic theoretical research and interdisciplinary collaborations worldwide, and enhancing activities in developing counties. If elected, I will make my contributions to these endeavours.


Alastair Young

Professor of Statistics, Department of Mathematics, Imperial College London

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Education

  • B.Sc. Mathematics and Statistics, University of Edinburgh, 1981
  • Diploma in Mathematical Statistics, University of Cambridge, 1982
  • Ph.D., University of Cambridge, 1987

Research Interests

  • Contemporary nonparametric inference: resampling methods, bootstrap, nonparametric likelihood
  • Approximation methods in statistics
  • Parametric likelihood theory
  • Objective Bayes
  • Selective inference

Previous Service to the Profession

  • 1988-1992 Royal Statistical Society Research Section Committee member
  • 1988-1994 Associate Editor, Journal of Royal Statistical Society, Series B
  • 1994-1998 Joint Editor, Journal of Royal Statistical Society, Series B
  • 1999-date Associate Editor, Biometrika
  • 2008-2012 Associate Editor, Statistica Sinica
  • 2008-2012 Associate Editor, Sankhya, Series A
  • 2010-2012 Chair, Committee of Professors of Statistics, UK and Ireland
  • 2011-2012 Member, RSS Academic Affairs Advisory Group
  • 2012-date Associate Editor, Journal of Statistical Planning and Inference
  • 2012-2013 Chair, Research Section Committee, Royal Statistical Society
  • 2013-date Associate Editor, Computational Statistics and Data Analysis
  • 2014-2017 Honorary Officer, Publications Theme, Royal Statistical Society
  • 2015-date Associate Editor, Bernoulli
  • 2015-date Associate Editor, Econometrics and Statistics
  • 2018-date Associate Editor, Journal of Royal Statistical Society, Series B

Brief Statement

It is a great honor to be nominated for membership of the IMS Council. In the era of data science, it is more important than ever that the statistics and probability community maintains the united focus the IMS offers. The Institute has a long-standing reputation for the excellence of its publications, its meetings, its mentoring of new researchers, especially women, and shaping of the discipline.  Its role and contributions deserve to be broadcast more loudly, especially outside North America.