We are pleased to announce the 25 new IMS Fellows selected in 2019. They will be presented at the IMS Presidential Address and Awards session at JSM, on Monday July 29: do join us!
Edoardo M. Airoldi, Co-Director, Data Science Institute, and Millard E Gladfelter Professor of Statistics & Data Science, Temple University: For methodological contributions to modeling network data and theoretical contributions to random geometric hypergraphs.
Cristina Butucea, Professor, ENSAE, Institut Polytechnique de Paris: For deep and original contributions to non-parametric statistics, inverse problems, and quantum statistics.
Victor Chernozhukov, International Ford Professor, Department of Economics and Center for Statistics & Data Science, Massachusetts Institute of Technology: For path-breaking contributions to high-dimensional inference.
Jeng-Min Chiou, Distinguished Research Fellow, Academia Sinica: For contributions to methodology for clustering, classification, and prediction with functional data.
Bertrand Salem Clarke, Professor and Chair of the Department of Statistics, University of Nebraska-Lincoln: For contributions to the theoretical justification of reference priors and on aspects of model selection involving Bayesian model averaging.
Michael Cranston, Professor, University of California, Irvine: For contributions to coupling techniques resolving significant open problems for Brownian motion and questions in mathematical physics.
Robert C. Dalang, Professor of Mathematics, École Polytechnique Fédérale de Lausanne: For pioneering contributions to the study of SPDEs driven by a Gaussian noise which is white in time with a spatially homogeneous covariance.
Christina Goldschmidt, Professor, University of Oxford: For fundamental contributions to the fields of coalescence and fragmentation theory, and to continuum limits for random trees and graphs.
Yongdai Kim, Professor, Seoul National University, Korea: For contributions to nonparametric Bayesian estimation for counting processes and high-dimensional regression.
Alois Kneip, Professor of Statistics, University of Bonn: For fundamental contributions to functional data analysis and nonparametric regression.
Shiqing Ling, Professor, Hong Kong University of Science and Technology: For contributions to the analysis of time series with heteroscedastic and heavy-tailed noise and goodness-of-fit tests for dependent data.
Jinchi Lv, Kenneth King Stonier Chair in Business Administration and Professor of Data Sciences and Operations, and Mathematics, University of Southern California: For contributions to high-dimensional statistics and causal inference.
Elizabeth S. Meckes, Professor of Mathematics, Case Western Reserve University: For contributions to Stein’s method and to random matrix theory.
Victor M. Panaretos, Professor of Mathematical Statistics, École Polytechnique Fédérale de Lausanne: For contributions to functional data analysis and stochastic geometry, in particular to estimation of spectral density kernels for stationary time series.
Victor Pătrângenaru, Professor of Statistics, Florida State University: For contributions to non-parametric statistics on manifolds and statistics for computer vision.
Debashis Paul, Professor, Department of Statistics, University of California, Davis: For contributions to non-parametric methods, high-dimensional multivariate analysis and random matrix theory.
Firas Rassoul-Agha, Professor, University of Utah: For contributions to central limit theorems and large deviations, random walks in random environments, random polymers, and related percolation models in statistical physics.
Bruno N. Rémillard, Professor, HEC Montréal: For contributions to copula modelling, to tests of independence, goodness of-fit testing, weak convergence tools for such inference, and to quantitative finance.
Adrian Röllin, Associate Professor, National University of Singapore: For the development of Stein’s method for multivariate cases including the unification of coupling under the name of Stein coupling.
Cynthia Rudin, Professor of Computer Science, Electrical and Computer Engineering, and Statistical Science, Duke University: For contributions to interpretable machine learning algorithms, prediction in large scale medical databases, and theoretical properties of ranking algorithms.
Xiaofeng Shao, Professor, University of Illinois, Urbana-Champaign: For contributions to non-parametric statistical inference for multivariate time series, in particular to the asymptotic theory for time series analysis via moments and cumulants.
Yuedong Wang, Professor, University of California, Santa Barbara: For contributions to non-parametric regression and computational statistics, in particular smoothing spline methodology for dependent observations and applications to bioinformatics and biomedical modeling.
Christopher K. Wikle, Curators’ Distinguished Professor and Chair, Department of Statistics, University of Missouri: For fundamental contributions to spatio-temporal modeling and Bayesian computation and inference, with influential applications to geophysical, ecological, and socio-demographic areas.
Hongquan Xu, Professor and Graduate Vice Chair of Statistics, University of California, Los Angeles: For contributions to experimental design, computer experiments, and functional data analysis, in particular to nonregular fractional factorial designs and spacefilling designs.
Xiangrong Yin, Professor of Statistics, University of Kentucky: For seminal work in high-dimensional data analysis and data mining, sufficient dimension reduction, and sufficient variable selection.
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