### 2020 Nominees

#### President-Elect Nominee

Krzysztof (Chris) Burdzy

Professor, Department of Mathematics, University of Washington

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Education

• M.A. in mathematics (1979) Maria Curie-Sklodowska University (UMCS), Lublin, Poland
• M.A. in statistics (1981) University of California, Berkeley
• Ph.D. in statistics (1984) University of California, Berkeley

Research Interests

• Probability: Brownian motion, couplings, branching processes
• Mathematical analysis: potential theory, spectral theory, PDE
• Mathematical physics: billiards, statistical mechanics, lattice models
• Philosophical foundations of probability

Previous Service to the Profession

• 1997-1999, Member of the Publications Committee of the IMS
• 1997-1999, Associate Program Secretary for Probability and Its Applications of the IMS
• 1999-2001, American Statistical Association Task Force on Electronic Publications, a representative of the IMS
• 1999, Chair of the Publications Committee of the IMS
• 2000-2004, Member of the IMS Electronic Issues Committee
• 2000-2002, IMS representative with project Euclid
• 2003-2009, Associate editor of Annals of Probability
• 2006-2009, Institute of Mathematical Statistics Web Editor
• 2006-2009, Council of the Institute of Mathematical Statistics, ex officio member (as the IMS Web Editor)
• 2009–2011, Associate editor of Annals of Applied Probability
• 2010-2013, Member of the Council of the IMS (elected)
• 2010-2013, Representative of the IMS on the Current Index to Statistics Management Committee
• 2011-2012, Member of the Special IMS-BS Nomination Committee for the Doob Lecture
• 2012-2014, Member of the Schramm Lecture Committee (representative of the IMS)
• 2012-2014, Editor, Annals of Probability
• 2012-2014, Member of the Council of the IMS (ex officio)
• 2012-2014, Member of the Committee on Publications of the IMS (ex officio)
• 2012-2014, Member of the Committee on Special Lectures of the IMS (ex officio)

Brief Statement

I am greatly honored by being nominated for the IMS President. Big Data presents both challenges for and opportunities to statistics. In my opinion, it also presents new opportunities for the statistical and probabilistic communities to get closer via the focus on the common scientific models. Electronic publishing went through a revolution in the last 30 years or so. It is a good time to reflect on how we are doing and try to anticipate how scientific publishing may evolve next. The IMS is widely known for publishing some of the best journals in the field. To retain this status, it is important to maintain (and increase, if possible) support for its activities among both junior statisticians and junior probabilists.

#### Council Nominees

Tony Cai

Daniel H. Silberberg Professor of Statistics, Department of Statistics, University of Pennsylvania

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Education

• Ph.D. in Statistics, 1996, Cornell

Research Interests

• High-dimensional statistics & large-scale inference
• Statistical machine learning
• Applications to genomics, chemical identification, and medical imaging

Previous Service to the Profession

• President, International Chinese Statistical Association, 2017
• Program Chair, IMS Annual Meetings  (2017 & 2007)
• COPSS Presidents’ Award Committee, 2009-2012, 2014; Chair, 2012
• Co-Editor, The Annals of Statistics,2010 – 2012
• Associate Editor, JRSSB, JASA, Annals of Statistics, Statistica Sinica
• Publications Committee, Bernoulli Society, 2011-2014
• Director of the Board of International Chinese Statistical Association, 2009-2011
• Committee on Special Lectures, Committee on Nominations, Committee to Select Editors, IMS

Brief Statement

The emergence of data science presents unprecedented opportunities and challenges to statisticians and also to IMS as a learned society. If elected, I will help promote the IMS as the foremost scientific society for researchers in statistics, machine learning, and probability, as well as a platform for interactions with data science researchers in applied sciences, high tech and financial industries.

Richard A. Davis

Howard Levene Professor of Statistics, Department of Statistics, Columbia University

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Education

• 1974: BA Mathematics, University of California at San Diego
• 1979: PhD Mathematics, University of California at San Diego

Research Interests

• Time series analysis
• Extreme value for stationary sequences and space-time processes
• Spatial statistics with application to environmental data
• Applied probability

Previous Service to the Profession

• IMS: Council (2013—2015); Carver Award Commttee (2017—present); Memorials Committee (2017-present)
• Foundation Committee for “The Prize in Statistics), IMS rep (2018-present)
• IMS President (2015/16)
• Joint IMS/Bernoulli Society Publications Management Committee (Jan 14-present)
• Editor-in-Chief, Bernoulli (Jan 10– Dec 12)
• Associate Editor, Annals of Applied Probability (Jan ’94–Jan ’00)
• Associate Editor, Extremes (Jan ’07 – present)
• Associate Editor, Bernoulli (Jan ’07 – Dec 08)
• Editor, Statistical Science (Jan ’08 – Dec 10)
• Associate Editor, Stochastic Processes and Their Applications (Jan ’93-Jan ’96, Mar 08– Jan `10)
• Business and Economics Statistics Section, Chair-elect (2009), Chair (2010)

Brief Statement

It is an honor to stand for election to the IMS council.  The strength of IMS is its engaged and dedicated membership of whom so many are willing to commit their time and expertise to the betterment of the society and the profession.  As an IMS council member, I would hope to follow in this tradition and provide sensible guidance and advice to the society.  I am especially keen for IMS to expand its support, via activities and opportunities, of early career researchers and under-represented groups.  This is an important component for the long-term health of both the society and our field.

Pablo A Ferrari

Emeritus Professor, Department of Mathematics, Universidad de Buenos Aires

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Education

• Doutor em Estatística, Universidade de São Paulo, 1982

Research Interests

• Interacting particle systems,
• Statistical mechanics,
• Random permutations,
• Cellular automata

Previous Service to the Profession

• Member of Committee for Conferences on Stochastic Processes of the Bernoulli Society;
• Organizer and member of several Brazilian Probability schools,
• Organizer of SPA Conference in Buenos Aires 2014.
• Organizer of CLAPEM (Latin American Congress in Probability and Mathematical Statistics) in Sao Paulo and in Lima,
• Member of scientific committee of several CLAPEM,
• Fellow of IMS and ISI;
• Associate Editor of Annals of Probability, Probability Theory and Related Fields, Electronic Journal of Probability, Journal of Statistical Physics, Annales de L’Institut Henry Poincaré, Revista de Matemática Aplicada (Chile), Revista de la Unión Matemática Argentina, ALEA – Latin American Journal of Probability and Mathematical Statistics, Bernoulli, Brazilian Journal of Probability and Statistics, São Paulo Journal of Mathematical Sciences.

Brief Statement

I am a probabilist working on interacting particle systems and statistical mechanics models. Collaboration between mathematical statisticians and probabilists is a crucial ingredient of modern research in both areas; one of the most important IMS goals is to foster this interaction. I intend to help strength the links between IMS and the Latin America Society for Probability and Mathematical Statistics, which is the Latin American Regional Committee of the Bernoulli Society.

Alice Guionnet

Directrice de recherche, Unite de Mathematiques Pures et Appliquées, CNRS-ENS de Lyon

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Education

• PhD, 1995, Université d’Orsay
• Habilitation, 2005, ENS de Lyon

Research Interests

• Probability
• Statistical physics
• Large random matrices
• Large deviations

Previous Service to the Profession

• Editor  of the Annales  de l’IHP, 2006 -2011
• Associate Editor for the Annals of probability,2011-2017
• Associate Editor SPA 1998-2001
• Associate Editor JAMS 2015–
• Associate Editor Annales de l’Institut Fourier 2019–
• Associate Editor Compte Rendu de l’Academie 2020–

Brief Statement

I believe that the IMS plays a central role to promote probability and statistics as a central field of mathematics. It is crucial that IMS maintains the high level of its publications and continues to make them affordable, being a role model for affordable journals. This means developing novel ways of publishing and assessing research, providing support to junior researchers, and guaranteeing an inclusive approach to research and dissemination.

Samuel Kou

Professor of Statistics, Department of Statistics, Harvard University

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Education

• Ph. D. in statistics, received from Stanford University in 2001

Research Interests

• Stochastic inference in single molecule biophysics, chemistry and biology
• Bayesian inference of stochastic models
• Big data and big data analytics
• Nonparametric methods, model selection and empirical Bayes
• Monte Carlo methods
• Economic and financial modeling

Previous Service to the Profession

• 2015. Committee on Nominations, Institute of Mathematical Statistics
• 2008 to 2011. Committee on Publications (served as committee chair: 2009 — 2010), Institute of Mathematical Statistics
• 2018. COPSS Presidents’ Award Committee
• 2017, 2016, 2014, 2013, 2012, and 2009. US National Science Foundation grant review panel
• 2010 to 2012. Member, Board of Directors, International Chinese Statistical Association
• 2019, 2018, 2015, and 2010. Guest Editor, Proceedings of the National Academy of Sciences of the USA
• 2017 to now. Associate Editor, Journal of the American Statistical Association, Theory and Methods
• 2013 to 2019. Associate Editor, Annals of Statistics
• 2010 to 2012. Editor, Annals of Applied Statistics, 2010 — 2012
• 2013 to 2017. Editor, STAT, 2013 — 2017
• 2011 to 2013. Associate Editor, Statistical Science, 2011 — 2013
• 2010 to 2014. Associate Editor, Bernoulli
• 2009 to 2012∙ Associate Editor, Journal of the American Statistical Association, Applications and Case Studies
• 2008 to 2013. Editor, Chance Magazine
• 2007 to 2009, and 2012 to 2015. Associate Editor, Annals of Applied Statistics
• 2005 to 2011, and 2014 to 2017. Associate Editor, Statistica Sinica
• 2006 to 2009. Associate Editor, Journal of Multivariate Analysis

Brief Statement

It is my great honor to be nominated for membership in the IMS Council. The IMS has an extraordinary tradition of bringing probabilists and statisticians together, with a united focus on scientific excellence, evidenced by its outstanding reputation on publications, meetings, promoting collaboration, and mentoring young researchers. The inclusive culture of the IMS is particularly well suited for shaping the discipline and fostering cross-fertilization in the era of data science, where a concerted effort (from statisticians and probabilists) is needed for important scientific applications as well as deep understanding of new technical advances. It will be my privilege to contribute to this effort.

Philippe Rigollet

Associate Professor, Department of Mathematics & Statistics and Data Science Center, Massachusetts Institute of Technology

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Education

• PhD in Mathematics, University of Paris 6 (2006)
• BSc in Statistics, University of Paris 6 (2002)

Research Interests

• Nonparametric and high-dimensional statistics
• Algorithmic aspects of statistical methods
• Geometric data analysis
• Statistical optimal transport
• Minimax optimality

Previous Service to the Profession

• Associate editor for:
• Mathematical Statistics and Learning (2018-21)
• SIAM Journal on Mathematics of Data Science (2018-21)
• Bernoulli (2013-19)
• Electronic Journal of Statistics (2016-19)
• Statistical Inference for Stochastic Processes (2015-16)
• Journal of Statistical Planning and Inference (2012-15)
• Conference on Learning Theory (COLT) steering committee (elected), 2013-16
• Program committee:
• COLT co-Chair (2018)
• COLT program committee member (2012-present)
• Algorithmic Learning Theory (ALT) program committee member (2015)
• Scientific committee:
• Testing and learning workshop, Simons Institute
• MIFODS workshop on learning under complex structure
• Oberwolfach workshop on Statistical and computational aspects of learning
• Skoltech conference on Statistical Optimal Transport
• MIFODS workshop on Sublinear Algorithms, MIT
• Stochastic Methods in Game Theory workshop, Singapore
• Optimization and Statistical Learning workshop, France
• Meeting on Mathematical Statistics workshop, France
• Conference on Learning Theory (COLT) (held at Princeton)
• International Workshop on Statistical Learning, Moscow
• Webmaster:
• Association for Computational Learning (runs COLT)

Brief Statement

The IMS is the premier society in statistics and probability, and I am honored to be nominated for membership of its council. The information era has witnessed an explosion in the size and diversity of data collected in a wide range of applications. Along with this expansion come new challenges and opportunities, in particular concerning the computational aspects of our methods. The IMS has already started an interdisciplinary agenda with statistics and probability at its core and I aim to reinforce it by supporting interdisciplinary meetings and opportunities for training new generations of researchers and teachers at this interface.

Martin Wainwright

Chancellor’s Professor, UC Berkeley, Department of Statistics, and Department of EECS, UC Berkeley

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Education

• B. Math, U. Waterloo (1994)
• Master’s Harvard (1999)
• Ph.D. MIT (2002)

Research Interests

• High-dimensional statistics
• Non-parametric statistics
• Information theory and statistics
• Statistical optimization
• Graphical models

Previous Service to the Profession

• IMS Committees:  Special Committee on Publications,
Awards Committee,  President Committee
• Associate Editorships:  Annals of Statistics (2008–2016),
Journal of Machine Learning Research (2007–2013), Journal
of the American Statistical Association (2013–2015)

Brief Statement

The advent of data science has provided Statistics with both tremendous opportunities and challenges moving forward.  We need to ensure that Statistics grows through engagement with other disciplines, while simultaneously preserving its rich intellectual history and scholarly traditions.  I am confident that my own background, which combines statistics with computer science, will provide useful perspective to the IMS Council in addressing these issues.

Anita Winter

Professor, Anita Winter, University Duisburg-Essen

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Education

• Diploma, Mathematics, 1995, Humboldt University Berlin
• PhD, Mathematics, 1999, University Erlangen-Nuremberg

Research Interests

• Branching models and its connections with population genetics and mathematical ecology
• Random trees
• Geometry of tree spaces and metric measure spaces
• Stochastic analysis on metric measure spaces

Previous Service to the Profession

• Board of the Probability and Statistics Section, German Mathematical Society (Member since 2016, speaker since 2018)
• Member of the Scientific Committee of the German Open Probability and Statistics Days, Freiburg 2018
• Member of the Scientific Committee of the German Open Probability and Statistics Days, Dresden 2020
• Member of the Local Organization Committee of the Bernoulli-IMS World Congress 2024

Brief Statement

It is a great honor to be nominated to the IMS Council. The institute has a united focus on probability and statistics, and an excellent reputation for its publications and its meetings. If elected, I  will keep and strongly promote its efforts towards diversity in gender, career stage, geography, background and research areas.

Fang Yao

Chair Professor, Department of Probability and Statistics, Peking University

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Education

• PhD, 2003, University of California at Davis

Research Interests

• Functional and longitudinal data analysis
• Statistical modeling of high-dimensional and complex structured data
• Nonparametric and semiparametric statistical methods
• Applications involving functional, high-dimensional and complex objects, e.g., clinical studies, evolutional biology, human genetics, brain imaging, finance and e-commerce, chemical engineering, etc.

Previous Service to the Profession

• IMS Nomination Committee (2017-2018),
• IMS Committee on Electronic Issues (2013-2016),
• Program Committee for 2012 JSM (IMS contributed sessions),
• ASA Noether Awards Committee (2014-2019),
• Chair for Student Paper Awards of ASA Section on Nonparametric Statistics (2011, 2012).
• Editor for Canadian Journal of Statistics (2019—present),
• Associate Editor for Statistica Sinica (2011–2014, 2017–present),
• Associate Editor for Journal of the American Statistical Association (2014–present),
• Associate Editor for Journal of Computational and Graphical Statistics (2012–present),
• Associate Editor for Canadian Journal of Statistics (2010–2018),
• Associate Editor for Journal of Multivariate Analysis (2016–2018),
• Associate Editor for The Annals of Statistics (2008–2009, 2013–2015),
• Associate Editor for Bernoulli Journal (2013–2015),
• Associate Editor for Journal of Statistical Planning and Inference (2012–2014),
• Associate Editor for Electronic Journal of Statistics (2010–2012).

Brief Statement

Fang Yao is a Chair Professor at Peking University, and has been a tenured Full Professor at University of Toronto. As an accomplished statistician, Fang Yao has received several awards, including the 2014 CRM-SSC Prize, which is considered the Canadian COPSS Award  (recognition of a statistical scientist’s professional accomplishments in research primarily conducted in Canada during the first 15 years after having received a doctorate).  In 2017 and 2018, he was elected the Fellow of the IMS, the Fellow of the ASA, and the Elected Member of ISI, respectively. He has been an excellent citizen of the statistical community by serving on key committees for IMS, ASA and other organizations, and serving on editorial boards for many statistical journals. He is a member of IMS, ASA, ICSA and SSC. Being in Peking University, one of the most reputable institutions in China/Asia, he will help increase the visibility and impact of IMS in Asia-Pacific region.

Ilze Ziedins

Associate Professor, Department of Statistics, The University of Auckland

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Education

• BA Waikato University 1980
• Diploma in Mathematical Statistics, University of Cambridge 1983
• PhD University of Cambridge 1989

Research Interests

• Stochastic networks, queueing networks.
• Selfish routing, priority assignment in networks.
• Applications of stochastic networks to healthcare delivery, communications and traffic networks

Previous Service to the Profession

• 2019 New Zealand Mathematical Society Accreditation Committee
• 2017-18 IMS Committee on Nominations
• 2013-15 Vice-President, Operations Research Society of New Zealand
• 2011-present Associate Editor, Queueing Systems
• 2002-07 Associate Editor, Stochastic Models
• 2002-2006 Associate Editor, Australian and New Zealand Journal of Statistics

Brief Statement

It is a great honour to be nominated for the Council of the IMS, and to have the opportunity to contribute to this wonderful community of probabilists and statisticians.  One of the strengths of the IMS is its very rich programme of sponsored meetings.  If elected, one of my particular interests would be to enhance the participation of members who have fewer opportunities to attend meetings, whether due to remoteness or for other reasons.