2022 Nominees

President-Elect Nominee

‪Michael Kosorok

W.R. Kenan, Jr. Distinguished Professor of Biostatistics and Professor of Statistics and Operations Research, Department of Biostatistics and Department of Statistics and Operations Research, University of North Carolina at Chapel Hill

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Education

  • BM Music Composition, 1988, Brigham Young University, Provo, Utah, USA
  • MS Statistics, 1988, Brigham Young University, Provo Utah, USA
  • MS Biostatistics, 1991, University of Washington, Seattle, WA, USA
  • PhD Biostatistics 1991, University of Washington, Seattle, WA, USA
  • MM Music Composition, 1999, University of Wisconsin-Madison, Madison, WI, USA

Research Interests

  • Biostatistics
  • Data Science
  • Empirical Processes
  • Machine Learning
  • Precision Medicine
  • Applications of Data Science to Biomedicine

Previous Service to the Profession

  • Associate Editor Annals of Statistics 2004-present
  • IMS Program Co-Chair, WNAR/IMS Joint Statistical Meeting 2002 Los Angeles
  • IMS Program Co-Chair,  ENAR/IMS Joint Statistical Meeting 2006 New Orleans
  • IMS Program Co-Chair, JSM 2009 Washington DC

Brief Statement

I feel honored to be nominated as President-Elect of the IMS, the premier professional society for statistics and probability. The IMS has a central role in the ongoing fundamental and interdisciplinary developments in science. I view this role broadly and to involve many facets, including data science, rigorous and reproducible research, interdisciplinarity, communication about science, and other aspects. My goals are to maintain the tremendous current strengths and initiatives of the IMS, as well as to grow relevant partnerships with greater inclusivity across the world and increased attention to professional development at all career stages, especially for young scientists.


Council Nominees

Siva Athreya

Professor, Department of Theoretical Statistics and Mathematics, Indian Statistical Institute

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Education

  • Bachelor of Science (Honours) Mathematics, (1991), St. Stephen’s College, New Delhi, India
  • Master of Statistics, (1993), Indian Statistical Institute,  Kolkata, India
  • PhD in Mathematics, (1998), University of Washington, Seattle, U.S.A.

Research Interests

  • Stochastic Analysis (Stochastic Partial Differential Equations and Stochastic Differential Equations)
  • Random walks among mobile traps
  • Random Graphs
  • Tree-valued Processes
  • Computational Epidemiology

Previous Service to the Profession

  • Organiser: Bernoulli-IMS One World Symposium 2020,August 24, 2020 – August 28, 2020
  • Program Chair:  The Bernoulli-IMS 10th World Congress in Probability and Statistics, July 13-July 19 2021
  • Editor-in-Chief: Electronic Communications in Probability 2021-23

Brief Statement

It is a privilege to be a member of the IMS and a great honour to be nominated for the IMS Council. The IMS plays a very important role in bringing together  probability and statistics researchers, supporting high-quality research,  training and development. My interests in the IMS include maintaining  the high quality of the journals supported by the IMS, dissemination of  research results with minimal costs, helping early-career researchers, and supporting underrepresented research groups in the IMS community. I am very much committed to promoting diversity (geography, gender  and science) in all activities of the IMS.


Rina Foygel Barber

Louis Block Professor, Department of Statistics, University of Chicago

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Education

  • BS Mathematics, Brown University, 2005
  • MS Mathematics, University of Chicago, 2009
  • PhD Statistics, University of Chicago, 2012

Research Interests

  • High-dimensional statistics
  • Selective inference
  • Distribution-free inference
  • Medical imaging

Previous Service to the Profession

  • Associate editor:
    • Annals of Statistics (2017-present)
    • Information and Inference (2017-2021)
    • SIAM Journal on Mathematics of Data Science (2018-present)
  • Awards committees:
    • 2022 Bernoulli Prize for an Outstanding Survey Article in Probability or Statistics
  • Other:
    • Co-organizer of the International Seminar on Selective Inference (2020-present)
    • Co-organizer of multiple workshops

Brief Statement

This is a very exciting and dynamic time for the field of statistics, and the IMS is critical in providing opportunities for members of our field to grow as researchers and educators, for the development of interdisciplinary research between statistics and related fields, and for supporting students and new researchers in statistics, particularly during the challenges of the pandemic. I am very honored to be nominated for the IMS council and hope to have the opportunity to contribute to the IMS’s mission of supporting our field and our community.


Gilles Blanchard

Professor, Institute of Mathematics, University Paris-Saclay

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Education

  • Ph.D. in mathematics/statistics, University Paris-Nord, 2001

Research Interests

  • Statistical aspects of machine learning
  • High-dimensional statistics
  • Multiple testing

Previous Service to the Profession

  • AE, Electronic Journal of Statistics (2007-2021)
  • AE, Annales de l’Institut Henri Poincaré: Probability and Statistics (2009-2020)
  • AE, Bernoulli (2016-)
  • AE, Annals of Statistics (2012-2018, 2022-)

Brief Statement

With the phenomenal growth and recognition of data science, I believe the role of the IMS as a lighthouse to our community is all the more important — as the maintainer of a proud intellectual tradition in the fields of probability and statistics, as well as in welcoming new opportunities with a discerning eye.  Scientific excellence should always be its primary objective. Particularly important in my view is the support of early-career scientists while promoting equity of gender and origin. I also welcome self-reflection on our role and responsibility as a community in the context of global climate crisis.


Alexandra Carpentier

Professor and chair for Mathematical Statistics and Machine learning, Institut for Mathematics, Department of natural sciences, University of Potsdam

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Education

  • M.Sc in Statistics and Economics, ENSAE Paris, 2009
  • M.Sc in Statistics, Probability theory and Finance, Universite Paris 7, 2009
  • PhD in applied mathematics, Universite Lille 1 and INRIA Lille Nord-Europe, 2012

Research Interests

  • Minimax high and infinite dimensional statistics
  • Sequential learning and bandit theory
  • Adaptive inference

Previous Service to the Profession

  • AE for Bernoulli (2019-present)
  • AE for Annals of Statistics (2020-present)
  • AE for SIAM Journal for Uncertainty quantification (2021-present)
  • AE for ESAIM (2021-present)
  • AC and PC for various conferences (NeurIPS, COLT, ICML, AISTATS, etc)

Brief Statement

The IMS plays a central role for the mathematical statistics community, and it is an honor to be considered for membership on the IMS council. The following topics are mostly important to me: continuing to guarantee the scientific quality of IMS journals, promoting diversity, supporting early career researchers, and finding new ways to work and interact together as a community at an international level – in particular in relation to the mobility challenges posed by Covid and climate change


Sayan Mukherjee

Professor, Statistical Science, Mathematics, Computer Science, Biostatistics & Bioinformatics, Duke University

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Education

  • MS 1996 Columbia
  • PhD 2001 from MIT
  • BSE 2002 Princeton

Research Interests

  • Bayesian methodology
  • Computational and statistical methods for statistical genetics, quantitative genetics, cancer biology, molecular ecology, and morphology
  • Discrete Hodge theory
  • Dynamical systems
  • Geometry and topology for inference
  • Machine learning
  • Stochastic geometry and topology
  • Foundations of uncertainty quantification

Previous Service to the Profession

  • Ten Lectures on Topological Data Analysis: NSF-CBMS Regional Conference Series in Probability and Statistics
  • IMS Invited Program Chair for 2018 Joint Statistical Meetings
  • Associate Editor roles:
    • SIAM Journal on Mathematics of Data Science
    • Foundations of Data Science
    • Journal of Machine Learning Research
    • Annals of Statistics
    • Electronic Journal of Statistics
    • Journal of Multivariate Analysis
    • SIAM Journal on Applied Algebra and Geometry
    • Annals of Applied Statistics
    • BMC Medical Genomics
    • IEEE Transactions on Computational Biology and Bioinformatics
  • Conference and workshop service:
    • Senior Program Committee: International Joint Conference on Arti cial Intelligence
    • Program Committee: Intelligent Systems in Molecular Biology
    • ICML Senior Area Chair
    • AIStats Area Chair
    • IMS Invited Sessions Chair: Joint Statistics Meeting
    • Session organizer for Geometry and Topology in Statistical Inference at ENAR
    • Senior Program Committee: Neural Information Processing Systems
    • Area chair: Arti cial Intelligence and Statistics
    • Organizer: IMA Worskshop on “Bridging Statistics and Sheaves”
    • Organizer: APS-INFORMS Session on “Statistical learning and dynamics”
    • Organizer: SIAM-AG Session on “Topological Data Analysis”
    • Organizer: JSM Session on “Geometric Data Analysis”
    • Organizer: ICERM Semester Program on \Topology in Motion”
    • Organizer: Stochastic Topology and Thermodynamic Limits at ICERM
    • Principal lecturer: NSF-CBMS Regional Conference Series
    • Organizer: Triangle Lectures in Combinatorics
    • Organizer: 65th Birthday Conference for Robert Wolpert
    • Organizer: Workshop on Sensing and Analysis of High-Dimensional Data
    • AMS Short course: Joint Mathematics Meeting
    • Organizer: SAMSI program on Low Dimensional Representations
    • Program committee: International Conference on Machine Learning
    • Program committee: Artificial Intelligence and Statistics
    • Organizer: Biological Applications of Machine Learning,
    • Senior program committee: International Conference on Machine Learning
    • Local organizer: SAMSI program on Random Matrices
    • Co-organizer: SAMSI program on Random Matrices and Computer Models
    • Coordinator: SAMSI program on Random Graphs and Stochastic Computation
    • Instructor: First School on Computational Cell Biology at University of Urbino
    • Instructor: Machine Learning Summer School at Toyota Technical Institute
    • Organizer: Workshop in bioinformatics at Neural Information Processing Systems

Brief Statement

The research purview of the IMS is very broad from probabilists to mathematical statistician to applied statisticians to machine learners. I am unique in that I am part of all of these communities. In addition, I feel statistics is currently going through a critical period as data science, machine learning and statistics adjacent fields are getting greater attention and in the view of some taking resources that have traditionally gone to statistics. I think it is vital in this time that we consider statistics as broadly as possible and integrate data science, machine learning, as well as other new fields into statistics. In addition, I strongly feel the link between probability and statistics has been great for both disciplines and we need to work to keep this link strong and bring in links to theoretical computer science and machine learning. In short, I strongly support interdisciplinary efforts of the IMS. In my view the most useful thing the IMS can do is support and help develop junior members and I am committed to better understanding what their needs are and how we can support them. The issue of diversity and equity is also of great importance for the IMS and having language, actionable items, as well as clarity on this topic is vital but not trivial.


Sofia Charlotta Olhede

Chair of Statistical Data Science, Institute of Mathematics, Ecole Polytechnique Fédérale de Lausanne (EPFL)

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Education

  • MSci in Mathematics Imperial College London 2000
  • PhD in Mathematics Imperial College London 2003

Research Interests

  • Analysis of networks
  • Analysis of point processes
  • Random fields & Time Series
  • Applications in ecology, geoscience, neuroscience and oceanography

Previous Service to the Profession

  • Member of SFI Ireland Centre for Data Analytics Scientific Advisory Board since 2019
  • Commissioner on 2019 Law Society of England and Wales Public Policy Technology and Law Commission – Algorithms in the Justice System. Commissioner with Law Society Vice President Christina Blacklaws and Professor Sylvie Delacroix
  • Member of the UK Office of National Statistics Data Science Campus Advisory Board since July 2018
  • UK Royal Society and British Academy Data Governance Working Group July 2016–June 2017
  • UK Royal Society Machine Learning Working Group Nov. 2015–May 2017
  • Science Committee Chair for the establishment of the Alan Turing Institute, the UK National Data Science Institute 2015-2016
  • Member of IMS Committee to select editors, 2013-2014
  • Associate Editor for the IEEE Trans. Signal Proc October 2009–October 2013
  • Associate Editor for the J. Royal Statistical Society Series B August 2007–August 2011
  • Member of the Research Section of the UK Royal Statistical Society July 2005– Dec. 2009

Brief Statement

I am delighted to be nominated as a member of IMS council. IMS brings together probabilists and statisticians, thus convening a unique set of expertise. I have considerable experience of collaborating with other disciplines, both personally, and in terms of larger data science efforts. It would be my pleasure to leverage this intra- and inter-disciplinary experience to foster cross-fertilization of scientific ideas in data science within the context of IMS, and to work to support the next generation of researchers in probability and statistics.


Debashis Paul

Professor, Department of Statistics, University of California, Davis

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Education

  • B.Stat., Statistics, Indian Statistical Institute, 1997
  • M.Stat., Statistics, Indian Statistical Institute, 1999
  • M.A., Statistics, University of California Santa Barbara, 2000
  • Ph.D., Statistics, Stanford University, 2005

Research Interests

  • High-dimensional statistics
  • Random matrix theory
  • Random dynamical systems
  • Neuroimaging
  • Spatial statistics

Previous Service to the Profession

  • Associate Editor of The Annals of Statistics (2013-2021), Bernoulli (2016-2018), Electronic Journal of Statistics (2016- ), Journal of Statistical Planning and Inference (2012- ) , Sankhya Series A (2012- ), Statistica Sinica (2009-2014). Guest editor of special issue of Computational Statistics and Data Analysis (2020-2021)
  • Member: Committee on IMS New Researchers’ Conference (2011-2013)
  • Member: Program/organizing committee member of 8+ symposia and workshops (including two BIRS workshops and one MATRIX workshop)

Brief Statement

It is a great honor for me to be nominated for election to the IMS Council. IMS has played an exemplary role in providing high-quality outlets for dissemination of statistical and mathematical research and creating open and equitable platforms for scholastic activities. I aim to be able to contribute to this great endeavor, by focusing especially on the following aspects: supporting under-represented communities and young researchers in building professional careers, improving participation of students and scholars from developing countries in IMS sponsored events, and increasing access to quality statistical education among a wider group of students.


Judith Rousseau

Professor of Statistics, Department of Statistics, University of Oxford

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Education

  • Graduated from University of Paris Diderot and from ENSAE, 1994
  • PHD from University of Paris 6 , 1997
  • Habilitation à Diriger des recherche : 2003 from Université Paris Descartes

Research Interests

  • Bayesian Statistics
  • High dimensional Statistics
  • Bayesian nonparametrics
  • Asymptotics
  • Computational Statistics and approximate Bayesian computation
  • Statistical machine learning
  • Networks
  • Latent variable models

Previous Service to the Profession

  • Co-editor of Bayesian Analysis
  • Associate editor of : EJS, AIHP
  • Former associate editor of : Annals of statistics, Bernoulli, JASA, ANZJS
  • Board member of the SNF (swiss national Foundation) [2018-2020]
  • Member of a number of committees for the International Society of Bayesian Analysis, including Chair of the prize committee, chair of the De Groot committee, chair of the Savage committee
  • Organization of a few conferences (Bayesian nonparametrics 2017, ISBA world meeting 2018) member of a number of scientific committees for conferences and chair of the EMS meeting (2022), chair of the SFDS meeting 2016

Brief Statement

International societies are key to the development and dissemination of science and IMS in particular is central to the community of statistics, probability and data science in general.  I very much enjoyed my experience as IMS program secretary which allowed me to learn and understand how the IMS works, its challenges together with its importance. With the rapid expansion of data science in the society, we,  as statisticians, are facing very exciting times with entirely new types of problems and greater interactions with other disciplines be them applied mathematics or various domains of science. In this landscape IMS has a key role to play and I would love to help again in the continuation of the support IMS provides to the community.


Ryan Tibshirani

Professor, Department of Statistics and Machine Learning Department, Carnegie Mellon University

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Education

  • B.S. in Mathematics, 2007, Stanford University
  • Ph.D. in Statistics, 2011, Stanford University

Research Interests

  • High-dimensional statistics
  • Nonparametric estimation
  • Distribution-free inference
  • Continuous optimization
  • Numerical analysis
  • Epidemic tracking and forecasting

Previous Service to the Profession

  • Associate Editor for the Journal of Machine Learning Research (2018-present), Annals of Statistics (2016-2020), Journal of American Statistical Society (JASA) (2019-2020), Biometrika (2013-2016), Statistical Analysis and Data Mining (2013-2016), and for NeurIPS, ICML, AISTATS (2014-2020)
  • Editorial Board for the Springer Series in the Data Sciences (2018-present)
  • Scientific Advisory Board for the Institute for Pure and Applied Mathematics (IPAM) (2019-present)
  • Steering Committee for Association for Computing Machinery-Institute of Mathematical Statistics (ACM-IMS) Conference on Foundations of Data Science (2019-2020)
  • Associate Chair for Joint Statistical Meetings (JSM) (2018)

Brief Statement

I am honored to be nominated for the council position. The IMS occupies a central place in our field. If elected, I would focus on finding ways that the IMS can (1) help encourage and improve reproducibility in the publication process, and bridge the gap between the publication models in (and value systems embodied by) statistics and machine learning; and (2) help young statisticians to make an impact (and be properly recognized and rewarded) in ways that are not traditionally rewarded academically.


Harrison H. Zhou

Professor of Statistics and Data Science, Department of Statistics and Data Science, Yale University

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Education

  • Ph.D. in Mathematics, 2004, Cornell University

Research Interests

  • Analysis of iterative algorithms
  • Bayesian nonparametrics
  • Network analysis
  • Large covariance matrices estimation
  • Asymptotic decision theory

Previous Service to the Profession

  • 2020, IMS Program Chair for Invited Talks at JSM
  • 2010-2018, Associate Editor, Annals of Statistics
  • 2013-2021, Associate Editor, Bernoulli
  • 2017-2019, Associate Editor, Statistical Science
  • 2015-2018, IMS Committee to select Editors (chair)
  • 2010-2012, IMS Committee to select Editors

Brief Statement

It is a great honor to be nominated for election to the IMS Council. In the past nine years I have served as the department chair at Yale to help with its transition from a statistics department to a department of statistics and data science. My experience during the transition might be valuable for the IMS community to further embrace and integrate with data science.