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2017 Nominees

President Elect Nominee

 

Xiao-Li Meng

Whipple V. N. Jones Professor of Statistics Dean of the Harvard University Graduate School of Arts and Sciences

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Education

  • 1990: Ph.D. in Statistics - Harvard University
  • 1987: M.A. in Statistics - Harvard University
  • 1986: Diploma in Graduate Study of Mathematical Statistics - Research Institute of Mathematics, Fudan University, Shanghai, P.R. China
  • 1982: B.S. in Mathematics - Fudan University, Shanghai, P.R. China

Research Interests

  • Statistical Theory and Principles toward the foundation of Data Science;
  • Multi-resolution Inferences, such as accumulating statistical evidence for individualized treatments (high resolution prediction) and dealing with partial prior knowledge (low resolution information);
  • Multi-phase Inferences, such as handling uncongeniality between data pre-processors (e.g., imputers) and data analysts and preserving information in a distributed pre-processing system;
  • Multi-source Inferences, such as comparing large observational datasets with small probabilistic samples and designing methods to gain combined information guided by bias-variance trade-off;
  • Philosophical and Foundational Issues in Statistics, such as connecting and the interplay between Bayesian, Fiducial, and frequentist (BFF) perspectives, and their extensions, including belief function;
  • Statistical Computing and Computational Statistics, such as Markov chain Monte Carlo, EM-type algorithms and their self-consistent generalizations, and user-friendly combining rules for multiple-imputation inference;
  • Signal Extractions and Uncertainty Assessments in natural, social, and medical sciences, such as in astronomy/astrophysics and in psychology/psychiatry;
  • Elegant Mathematical Statistics, especially distribution theory and stochastic algebra.

Previous Service to the Profession

  • 2009 –2014 Editor, Statistics Series, IMS/CUP (Cambridge University Press) Monograph and Textbook Series
  • 2006 – 2009 and 2012 – 2015 IMS Council
  • 2005 – 2007 IMS Committee on Special Lectures
  • 2003 – 2005 IMS Committee on Nominations
  • 1998 – 1999 Chair, IMS Program Committee for the 1999 JSM
  • 1996 – 1997 IMS Program Committee for the 1997 ENAR Spring Meeting
  • 1995 Co-organizer, IMS/ASA invited panel on “Speeding the Referee Process”

Brief Statement

By now, most would agree that Data Science, seen from the angle of science for data, has two main pillars: Computer Science and Statistics, with Probability as their shared language.  The IMS, being the premiere society in Statistics and Probability worldwide, therefore, should lead in building and shaping the foundation of Data Science. It can do so by organizing and promoting fundamental research on core issues of Data Science, e.g., optimal trade-offs between computational efficiency and statistical efficiency. It can do more in attracting, training, and promoting of young talent, as young as high school students, who can enhance the IMS as an attractor and hub of the deepest and most communicative scholars of Data Science. This is also the perfect time to renew the vow of the long (but not always affectionate) marriage between Statistics and Probability. If elected, I’ll devote myself to this trio of goals to earn your trust.

Council Nominees

 

Gérard Biau

Professor, Theoretical and Applied Statistics Laboratory, University Pierre and Marie Curie, Paris, France

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Education

  • PhD in Statistics, 2000, Montpellier University, France

Research Interests

  • Nonparametric statistics
  • Statistical learning
  • Massive and high-dimensional data
  • Analysis of algorithms

Previous Service to the Profession

  • 2015-present President, French Statistical Society
  • 2013-present Director, Theoretical and Applied Statistics Laboratory, University Pierre and Marie Curie, Paris, France
  • 2013-present Co-editor-in-chief, ESAIM: Probability and Statistics

Brief Statement

It is an honor for me to stand as candidate for the IMS Council. Statistics and Probability are today at an unprecedented turning point in their common history, through the advent of what we now call data science. More important than ever, our disciplines must adapt in order to be able to meet the challenges of tomorrow's digital society. Given its history and global impact, the IMS seems to me to be the ideal vehicle for defending and affirming the importance of statistics and its deep mathematical roots, while accompanying its rapprochement with computing and more applied sciences. If elected, I intend to promote the development of statistics and probability, especially among younger people, while at the same time encouraging an opening up to new and interesting areas.

Jeng-Min Chiou

Research Fellow and Acting Director, Institute of Statistical Science, Academia Sinica

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Education

  • PhD in Statistics, 1997, University of California, Davis
  • MS in ISyE,1993, Georgia Institute of Technology
  • MS in Industrial Engineering,1989, National Tsing Hua University, Taiwan
  • BBA in Transportation, 1987, National Chiao Tung University, Taiwan

Research Interests

  • Functional data analysis, longitudinal data analysis
  • Semi-parametric methods, quasi-likelihood and estimating equations
  • Traffic flow analysis, Intelligent Transportation Systems
  • Statistical methods in aging
  • Biostatistics

Previous Service to the Profession

  • Co-editor, Statistica Sinica (2011-2014)
  • Managing Editor, Statistica Sinica (2008-2011)
  • Associate Editor, Bernoulli Journal (2014-2015), Biometrics (2006-2010), CSDA (since 2015)
  • Council member, Bernoulli Society (2015-2017)
  • Co-Chair, 2016 CMStatistics
  • Panel Chair of Statistics, Taiwan Ministry of Science and Technology (2014-2016)
  • Board member, IMS-APRM programs (2012, 2014)
  • Program Committee, ICSA (2011-2013)

Brief Statement

The IMS has played a central role in an international society of probability and statistics. It is essential to make efforts to continue the excellence of the IMS and maintain the current high quality of IMS meetings and publications. The proactive interplay between theoretical and applied aspects of statistics is of vital importance to advance statistical science. The fast-growing field of data science brings us new challenges, including statistical training and education accompanied by the contemporary development and data-intensive interdisciplinary research. It would be an honor for me to serve the IMS and work toward these goals.

Mathias Drton

Professor, Department of Statistics, University of Washington

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Education

  • Ph.D. in Statistics, 2004, University of Washington, Seattle, U.S.A.
  • Diplom in Applied Math, 2000, Universität Augsburg, Germany
  • DEA in Applied Math, 1999, Université Paul Sabatier, Toulouse, France

Research Interests

  • Graphical models
  • Algebraic statistics

Previous Service to the Profession


  • Associate Editor, Annals of Statistics, 2008-2016
  • Associate Editor, Electronic Journal of Statistics, 2012-present
  • Associate Editor, JRSS B, 2007-2011
  • Chair, Member, IMS Committee on Special Lectures
  • Member, IMS Committee to Select Editors
  • IMS Program Chair, WNAR 2012

Brief Statement

I am honored to be nominated for a position on the IMS Council. The IMS has been my academic home ever since I joined the society as a graduate student. Through its outstanding journals, meetings, and guidance to young researchers it has played an important role in my professional development. If elected to the Council, I will work to help maintain and expand the mentorship the society provides to junior researchers, to promote the society's journals and conferences, and to strengthen the society's international and interdisciplinary presence.

Tadahisa Funaki

Professor, Graduate School of Mathematical Sciences, University of Tokyo

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Education

  • Ph.D. in Mathematics, 1982, Nagoya University

Research Interests

  • Probability theory, stochastic analysis
  • Stochastic partial differential equations
  • Large scale interacting systems, scaling limits
  • Random interfaces

Previous Service to the Profession


  • President: Mathematical Society of Japan (2013—2015)
  • Associate Editor: Annals of Probability (1994—2000); Annales de l'Institut Henri Poincaré, Probabilités et Statistique (2005—2012); Probability and Mathematical Statistics (2006—2010); Stochastic Partial Differential Equations: Analysis and Computations (2012—); Forum of Mathematics, Pi and Sigma (2012—)
  • Scientific Committees of Conferences on Stochastic Processes and Their Applications: 30th (Santa Barbara, 2005), 34th (Osaka, 2010), 37th (Buenos Aires, 2014)
  • Member of Committee for Conferences on Stochastic Processes, Bernoulli Society (2001—2009)

Brief Statement


It is an honor for me to have been nominated as a candidate for the IMS Council. The purpose of the IMS is to foster the development and dissemination of the theory and applications of statistics and probability. Needless to say, interdisciplinary relations to other areas of mathematics, sciences, and industries increase and the activities are expanding worldwide. Japan has in particular a long tradition in modern probability originated with Kiyosi Itô. If elected to the council, I would be privileged to serve the IMS and promote its activities.

Bénédicte Haas

Professor, LAGA (Laboratoire d'Analyse Géométrie et Applications), Université Paris 13, France

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Education

  • PhD in Mathematics, 2004, University Paris 6

Research Interests

  • Probability theory
  • Random trees
  • Fragmentation processes
  • Self-similar Markov processes

Previous Service to the Profession

  • Associate Editor, ESAIM Probability & Statistics (2013 - present)
  • Member of the scientific committee of the 40th SPA conference (Chalmers 2018)

Brief Statement

I believe the IMS is an important organization for our community, which does an excellent job (for example, through the journals and conferences it provides). I would be happy and honored to contribute to its various actions, to commit myself to the community and to give back what I benefited from. In particular, I would like to focus on the following issues, which I currently find among the most important: the careers of our young colleagues; gender issues;  promotion of probability and statistics.

Peter Hoff

Professor, Department of Statistical Science, Duke University

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Education

  • Ph.D. in Statistics, University of Wisconsin, 2000
  • M.S. in Statistics, University of Wisconsin, 1994
  • B.S. in Mathematics, Indiana University 1993

Research Interests

  • Multivariate statistics
  • Bayes and empirical Bayes methods
  • Matrix and tensor-valued data

Previous Service to the Profession

  • Associate Editor, Annals of Applied Statistics, 2006-present.
  • Associate Editor, Statistical Science, 2011-2015.
  • Associate Editor, Journal of the Royal Statistical Society, Series B, 2009-2013.
  • ISBA Board of Directors, 2010-2012.
  • Editorial Board Member, SIAM Classics, 2008-2010.

Brief Statement

The primary service provided by the Institute is the dissemination of new ideas and results to the statistics community and beyond. While the current journal system may work well for many authors and audiences, younger statistical researchers are increasingly accessing and disseminating information using alternative systems, typically ones centered in other communities of the mathematical sciences. To ensure that Statistics maintains a strong position in the quantitative sciences, we should explore new approaches to scholarly dissemination that complement the existing journal system and that reflect recent changes to how people access and distribute information.

Gregory F. Lawler

George Wells Beadle Distinguished Service Professor in Mathematics and in Statistics University of Chicago

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Education

  • 1979: Ph.D., Princeton University
  • 1976: B.A., University of Virginia

Research Interests

  • Brownian motion and random walk
  • Models in statistical physics
  • Connections between complex analysis and probability
  • Critical phenomena and random fractals

Previous Service to the Profession

  • Co-founder, Electronic Journal of Probability, 1995
  • Organizer, Seminar on Stochastic Processes, 1996, 2005
  • IMS Committee on Fellows, 1997-2000 (chair 1999-2000)
  • American Mathematical Society (AMS) Editorial Boards Committee, 2000-2002 (chair 2002)
  • Editor, Annals of Probability (2006-2008)
  • Editor, Journal of AMS, 2009-2013
  • AMS Committee on Publications (2009-2011, chair 2011)
  • Scientific Research Board, American Institute of Mathematics, 2006--2010
  • Scientific Review Panel, Pacific Institute for the Mathematical Sciences, 2010-2014
  • Scientific Advisory Committee, Mathematical Sciences Research Institute, 2014 --
  • AMS short course committee (2015 -- )
  • AMS Council, 2017 --

Brief Statement

While both probability and statistics are exciting research fields today, the frontiers of research keep getting farther apart. Both fields are interacting much more with other areas of mathematics and computer science. Perhaps it is time for the IMS to consider whether it makes sense to stay a a single society.

Antonietta Mira

Professor of Statistics and co-director, InterDisciplinary Institute of Data Science, Università della Svizzera italiana, Lugano, Switzerland and Università dell’Insubria, Como, Italy

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Education

  • Master (1996) and PhD (1998) in Statistics, University of Minnesota, US
  • Doctorate in Methodological Statistics (1995), University of Trento, Italy

Research Interests

  • Computational statistics
    • Markov chain Monte Carlo methods
    • Adaptive importance sampling
    • Population Monte Carlo and particle filters
    • Perfect simulation, Slice sampler
    • Computational algorithms for doubly intractable problems
    • Approximate Bayesian Computation
  • Bayesian methodology
    • Exponential Random Graph and generalizations
    • Mixture models, Latent variable models, hidden Markov models and graphical models
    • Nonparametric approach
    • Model comparison via Bayes factor
  • Data Science
    • Analysis of social networks and relational data
    • Computational algorithms and models for complex / high frequency data

Previous Service to the Profession


  • Board member of the ISBA Section on Bayesian Computation: elected for the term 2013-14 and re-elected for the term 2015-16
  • Member of the ISBA council: elected for the term 2011-13
  • Member of the Savage Award Selection Committee (2003-05 and 2010-11) of ISBA
  • Member of the scientific program committee (co-chair) and of the organizing committee (chair) of the second (2005), third (2008), fourth (2011), fifth (2014) and sixth (2016) joint international meeting IMS/ISBA, Institute of Mathematical Statistics/International Society for Bayesian Analysis Meeting
  • Member of the scientific committee of the international (6 days) workshop on Challenges and Advances in High Dimensional and High Complexity Monte Carlo Computation and Theory, Banff (Canada), International Research Station for Mathematical Innovation and Discovery, 2012
  • Member of the scientific committee of the (3 days) workshop on Advances in Markov Chain Monte Carlo: Theory, Methodology and Applications, Edimburgo (April 2012)
  • Member of the scientific committee of the second Festival of Statistics and Demography, Treviso, Italy, 2016
  • Co-Editor Bayesian Analysis, 2008-16
  • Associate Editor of the Journal of Computational and Graphical Statistics, 2006-08
  • Associate Editor for Statistica Sinica, 2005-08

Brief Statement


It is a great honor to be nominated as candidate for the IMS council. If elected I would help the IMS promote the fundamental role of probability and statistics in the area of data science building/strengthening links with neighboring fields, with the aim of following the whole value chain from data to uncertainty quantification and information retrieval, all the way to actionable knowledge. This can be achieved, among other things, by maintaining the excellent quality of publications and conferences sponsored by the IMS and attracting young talents to the field, motivating them to become IMS members.

Axel Munk

Director, Felix-Bernstein Institute for Mathematical Statistics in the Biosciences, Georg-August Universität Göttingen and Max Planck Institute for Biophysical Chemistry

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Education

  • 1999 Habilitation, Ruhr Universität Bochum
  • 1994 Dr. rer nat. Georg-August Universität Göttingen
  • 1992 Diploma in Mathematics, Georg-August Universität Göttingen

Research Interests


  • Statistical inverse problems
  • Statistical image and signal recovery
  • Shape analysis
  • Optimal transport
  • Biometric identification
  • Statistics in biophysics and molecular biology

Previous Service to the Profession

  • Associate editor for:
    • Annals of Statistics (2009 -2012, 2016- )
    • Bernoulli (2012 -- )
    • Journal of the Royal Statistical Society, Series B (2013 - 2016)
    • Journal of Nonparametric Statistics (2008 - )
    • Journal of Statistical Planning and Inference (2012 - 2016)
    • Metrika (2008 - 2012)
    • Statistics & Risk Modeling (2008 - 2014)
    • Electronic Journal of Statistics (2016 - )
  • Council work:
    • Member of the European Regional Council of the Bernoulli Society (2008-2012)
    • Steering Committee Member of the International Society for Nonparametric Statistics (ISNPS)
  • Conference Organization and Program Committees (selection):
    • Statistical and Probabilistic Methods of Model Selection, 2005, Mathematical Research Center Oberwolfach
    • 7th World Congress in Probability and Statistics, 2008, Singapore
    • SIAM Conference on Imaging Science, 2008, San Diego
    • 1st International Society for Nonparametric Statistics (ISNPS). Invited session on 2012, Chalkidiki
    • Frontiers in Nonparametric Statistics, 2012, Mathematical Research Center Oberwolfach
    • European Meeting of Statisticians, 2013, Budapest
    • Adaptive Statistical Inference,  2014, Mathematical Research Center Oberwolfach
    • MSR/IMS workshop on Data Science. 2015, Microsoft Research, Boston
    • Recovery of Invariant Structures, 2017, Mathematical Research Center Oberwolfach

Brief Statement


Serving for the IMS council is a great responsibility and honor. Promoting rigorous statistical and probabilistic thinking, modeling and analysis in the era of ‘big data’ appears to be a key challenge nowadays. If elected, I envision strengthening the role of the IMS further in this direction. As a most prominent institution responsible for highest quality journals and conferences in probability and statistics, it is of utmost importance that it continues to play a central role in large scale data analysis, among others. Furthermore, I will put my efforts into strengthening the scientific bridge between the continents, particular among young researchers, which I feel is of particular importance these days.

Byeong Park

Professor, Department of Statistics, Seoul National University

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Education

  • Ph.D. - 1987, University of California, Berkeley
  • M.S. - 1984, Seoul National University
  • B.S. - 1982, Seoul National University

Research Interests

  • Nonparametric function estimation
  • Semiparametric inference
  • Functional data analysis
  • High-dimensional models
  • Machine learning

Previous Service to the Profession

  • Chair, Local Organizing Committee, The 1st IMS Asia Pacific Rim Meeting, 2009
  • Co-Chair, IMS Committee on Asia and Pacific Rim Meeting, 2009-2014
  • Theme Day Co-Organizer, 59th World Statistics Congress (ISI), Hong Kong, 2013
  • Scientific Program Committee (Bernoulli Society Representative), 60th World Statistics Congress (ISI), Rio de Janeiro, 2015
  • Chair, Short Course Program Committee, 61th World Statistics Congress (ISI), Marrakech, 2017
  • Co-Chair, the 8th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics), London, 2015
  • Ordinary Council member, Bernoulli Society, 2013-2015
  • Elected Council member, International Statistical Institute, 2013-2017
  • Scientific Secretary, Bernoulli Society, 2015-present
  • Associate Editor, Annals of Statistics, 2007.01-2009.12 & 2013.01-present
  • Associate Editor, Journal of American Statistical Association, 2017.01-present
  • Associate Editor, Latin American Journal of Probability and Mathematical Statistics, 2016.01- present
  • Associate Editor, Journal of Nonparametric Statistics, 2003-present
  • Associate Editor, Annals of Institute of Statistical Mathematics, 2006-present
  • Editor-in-Chief, Journal of Korean Statistical Society, 2008.01-2016.12
  • Co-Editor, Computational Statistics and Data Analysis, 2016.10-present

Brief Statement

The IMS has been faithful to its traditional roles of fostering the development of mathematical statistics and probability through high quality scholarly publications and scientific conferences. In this era of information technology, it needs to promote statistics and probability in many new emerging interdisciplinary areas. To strengthen its position as the leading international society for statisticians and probabilists, the IMS should also make a genuine effort to become truly global and increase its presence worldwide significantly, particularly in under-represented regions with growing research communities of statistics and probability. If elected, I would endeavor to help the IMS accomplish these missions.

Gesine Reinert

Professor, Department of Statistics, University of Oxford

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Education

  • Ph.D., 1994, University of Zurich, Switzerland

Research Interests

  • Applied probability, in particular Stein's method
  • Network analysis
  • Computational biology

Previous Service to the Profession

  • 2012-15 IMS Nomination Panel
  • Since 2016, Chair of the IMS Committee to Select Administrative Officers
  • Associate editor, Journal of Applied Probability
  • From 2010-2015 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. There are very fertile areas to be explored at the boundaries of statistics, including the boundary to decision making, the boundary to sciences such as biology and the boundary to probability. The inclusive approach of the IMS fosters such research across disciplines, in particular supporting early career researchers, and it would be a privilege to contribute to this endeavour.

Chiara Sabatti

Professor, Biomedical Data Science and Statistics, Stanford University

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Education

  • Ph.D in Statistics, 1998, Stanford University
  • BS in Economic and Social Disciplines, 1993, Bocconi 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 an 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 “it speaks for itself” nor developing an indiscriminate and disabling skepticism.