Congratulations to the 2024 Class of IMS Fellows!

The designation of IMS Fellow has been a significant honor for almost 90 years. Each Fellow has demonstrated distinction in research in statistics or probability or has demonstrated leadership that has profoundly influenced the field.

Genevera I. Allen
Columbia University
For groundbreaking research in graphical models, feature selection, unsupervised learning, and data integration and leadership in data science education.

Jacob Bien
University of Southern California
For methodological contributions to the field of statistics that emphasize interpretability, computational efficiency, and relevance to scientific disciplines.

Malgorzata Bogdan
Lund University, University of Wroclaw
For innovative contributions to high-dimensional statistics with a focus on multiple testing and variable selection, insightful connections between Bayesian and Frequentist statistics, and leadership in forging scientific collaborations across geographical areas and fields of study.

Tamara Broderick
Massachusetts Institute of Technology
For significant contributions to theoretical modeling and computational methodology at the intersection of Bayesian Statistical Machine Learning and Bayesian nonparametric theory and applications.

Catherine A. Calder
University of Texas at Austin
For original research contributions in statistical methods for the analysis of spatio-temporal data; for leadership in data-driven substantive research in environmental, geophysical, and social sciences; and for outstanding service to the profession.

Xi Chen
New York University
For notable contributions to statistical inference and applications for online, distributed, and high-dimensional data.

Yuguo Chen
University of Illinois Urbana-Champaign
For contributions to SIS and Sequential MC approaches with a focus on categorical data and other discrete structures and for contributions to dynamic network model including the development of community detection methods using multi-layer networks.

Juan A. Cuesta-Albertos

Universidad de Cantabria
For outstanding contributions to statistics and probability, including the areas of optimal transport, robust statistics, data depth, classification, and their applications.

Josée Dupuis
McGill University
For fundamental contributions to the field of statistical genetics, in detecting complex traits and interactions, for mentoring, and for leadership in the statistics and genetics communities.

Emily B. Fox
Stanford University
For broad-ranging and highly impactful seminal work on large-scale Bayesian dynamic modeling, sparse network models, and related development of efficient computational algorithms for Bayesian inference, and for applications in health and the study of biomedicine. algorithms for Bayesian inference.

Debashis Ghosh
University of Colorado Anschutz Medical Campus
For outstanding foundational contributions to statistical methodologies for biomedical data analysis, for impactful collaborations on cancer genomics and beyond, and for exceptional dedication to community service and mentorship.

Maria Gordina
University of Connecticut
For fundamental contributions to stochastic analysis and stochastic differential geometry, and for service to the profession.

Kengo Kato
Cornell University
For fundamental contributions to high-dimensional central limit theorems and bootstrapping, including those for U-statistics and data with complex dependence structures, their applications to nonparametric statistical models, quantile regression, and statistical optimal transport.

Christina Kendziorski
University of Wisconsin – Madison
For the sustained, impactful contributions to statistics in genomics for more than 20 years, the outstanding record of mentoring women statisticians, and service to the profession.

Fan Li
Duke University
For seminal contributions to the statistical foundation of causal inference and missing data, for innovative statistical applications in observational studies, and for outstanding services to statistical communities.

Shili Lin
Ohio State University
For excellent research in methodological and computational statistical genetics and genomics and applications to human diseases; for leadership in mentoring students and junior researchers; and for outstanding service to the profession.

Zongming Ma
Yale University
For groundbreaking contributions to modern statistical theory with theory-informed applications in single-cell biology.

David S. Matteson
Cornell University and the National Institute of Statistical Sciences
For fundamental contributions to statistical theory and applications, including multiple R packages and machine learning, and for important contributions to data science and excellent services to the statistical profession.

Ilya Molchanov
University of Bern
For innovative contributions to probability theory and statistics, particularly in the analysis of random sets, the estimation of level sets, and curves with applications to image analysis, econometrics, and finance

Hernando Ombao
King Abdullah University of Science and Technology
For contributions to time series modeling and spectral analysis of biological data, novel dependence measures for understanding brain connectivity, and training graduate students and post-doctoral scholars.

Edsel Aldea Pena
University of South Carolina
For important theoretical and methodological contributions in event time data analysis, multiple decision-making, reliability theory and methods, goodness-of-fit, and model validation; for mentoring graduate students; and for exemplary and dedicated service to the statistics profession.

J. Sunil Rao
University of Minnesota, Twin Cities
For important and novel contributions to high-dimensional model selection, for the development of new statistical and machine learning methods for the analysis of cancer genomic data, and for significant and sustained leadership in academia and the profession.

Johannes Schmidt-Hieber
University of Twente
For pioneering work on the statistical foundations of deep learning and fundamental contributions to spot volatility estimation, nonparametric inference under shape constraints, high-dimensional Bayesian inference, Le Cam theory, and inverse problems.

Haipeng Shen
HKU Business School
For exceptional contributions to theoretical advancements and influential applied research, particularly in the realms of data-driven decision-making amidst uncertainty, and for unwavering commitment to educational innovation and long-standing dedication to advancing the field of statistics.

Yu Shen
UT MD Anderson Cancer Center
For novel contributions to the methodology of complex survival data analysis, adaptive clinical trial designs, and cancer screening data modeling; for substantial collaboration impacting on the practice of medicine and public health recommendations.

Xinyuan Song
The Chinese University of Hong Kong
For outstanding contributions in statistical methodology, notably in structural equation and latent variable models, and their applications in psychometrics and for providing remarkable service and educational leadership within the statistical community.

Leonard A. Stefanski
North Carolina State University
For seminal contributions to measurement error models, deconvolution, variable selection, and extensive editorial work and service to the profession.

Stilian Atanasov Stoev
University of Michigan, Ann Arbor
For influential contributions in the modeling and analysis of stochastic processes with long-range dependence and heavy tails and for important contributions to extreme value theory, max-stable processes, and statistics of extremes.

Lei Sun
University of Toronto
For important contributions to statistical genetics, including developing new theories and methods that have enabled scientific breakthroughs in understanding the genetic basis of disease, and for exceptional contributions to leadership and training in collaborative research.

Joel A. Tropp
Caltech
For groundbreaking algorithms and theoretical insights that have profoundly influenced computational statistics and signal processing.

Caroline Uhler
Massachusetts Institute of Technology; Broad Institute of MIT and Harvard
For interdisciplinary excellence, merging mathematical statistics and computational biology in innovative and impactful ways.

Venugopal Veeravalli
University of Illinois at Urbana-Champaign
For influential contributions to sequential hypothesis testing and quickest change detection, and for service to the profession.

Lingzhou Xue
The Pennsylvania State University
For influential contributions to the methodology, theory, and application of high-dimensional statistics, statistical machine learning, and nonparametric statistics; for outstanding contributions and leadership in cross-disciplinary research; and for dedicated service to the profession.

Piotr Zwiernik
University of Toronto
For outstanding contributions to the theory of graphical models, exponential families, multivariate positive dependence, and dedicated editorial and organizational service to the profession.