Stephen Elliott Fienberg was a professor emeritus in the Department of Statistics, the Machine Learning Department, Heinz College, and Cylab at Carnegie Mellon University. Fienberg was the founding co-editor of the Annual Review of Statistics and Its Application and of the Journal of Privacy and Confidentiality.
Donald Bruce Rubin is an Emeritus Professor of Statistics at Harvard University, where he chaired the department of Statistics for 13 years. He also works at Tsinghua University in China and at Temple University in Philadelphia.
Lawrence David (Larry) Brown was Miers Busch Professor and Professor of Statistics at the Wharton School of the University of Pennsylvania in Philadelphia, Pennsylvania. He is known for his groundbreaking work in a broad range of fields including decision theory, recurrence and partial differential equations, nonparametric function estimation, minimax and adaptation theory, and the analysis of census data and call-center data.
Tianwen Tony Cai is a Chinese statistician. He is the Daniel H. Silberberg Professor of Statistics and Vice Dean at the Wharton School of the University of Pennsylvania. He is also professor of Applied Math & Computational Science Graduate Group, and associate scholar at the Department of Biostatistics, Epidemiology & Informatics, Perelman School of Medicine, University of Pennsylvania. In 2008 Tony Cai was awarded the COPSS Presidents' Award.
Rahul Mukerjee is an Indian academic and statistician. He is a National Science Chair of the Government of India, hosted by the Indian Institute of Management Calcutta, after his superannuation from the same institute in 2021 as a professor in the higher academic grade. He is also an emeritus scientist of the Indian National Science Academy, New Delhi.
Xiao-Li Meng is a Chinese American statistician and the Whipple V. N. Jones Professor of Statistics at Harvard University. He received the COPSS Presidents' Award in 2001. He has written numerous research papers about Markov chain Monte Carlo algorithms and other statistical methodology.
Jun S. Liu is a Chinese-American statistician focusing on Bayesian statistical inference, statistical machine learning, and computational biology. He was assistant professor of statistics at Harvard University from 1991 to 1994. From 1994 to 2004, he was Assistant, Associate, and full Professor of Statistics at Stanford University. Since 2000, Liu has been Professor of Statistics in the Department of Statistics at Harvard University and held a courtesy appointment at Harvard T.H. Chan School of Public Health.
Trevor John Hastie is an American statistician and computer scientist. He is currently serving as the John A. Overdeck Professor of Mathematical Sciences and Professor of Statistics at Stanford University. Hastie is known for his contributions to applied statistics, especially in the field of machine learning, data mining, and bioinformatics. He has authored several popular books in statistical learning, including The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Hastie has been listed as an ISI Highly Cited Author in Mathematics by the ISI Web of Knowledge.
Xuming He is Professor and Inaugural Chair of Statistics and Data Science at the Washington University in St. Louis. He serves as President (2023-2025) of the International Statistical Institute.
Eric Poe Xing is an American computer scientist whose research spans machine learning, computational biology, and statistical methodology. Xing is founding President of the world’s first artificial intelligence university, Mohamed bin Zayed University of Artificial Intelligence (MBZUAI).
David Bennett Madigan is an Irish–American statistician and academic. He is currently Provost and Senior Vice-President for Academic Affairs at Northeastern University. Previously he was Professor of Statistics at Columbia University. From 2013 to 2018 he was also the Executive Vice-President for Arts and Sciences and Dean of the Faculty of Arts and Sciences and from 2008 to 2013 he served as Chair of the Department of Statistics, both at Columbia University. He was Dean of Physical and Mathematical Sciences at Rutgers University (2005–2007), Director of the Institute of Biostatistics at Rutgers University (2003–2004), and Professor in the Department of Statistics at Rutgers University (2001–2007).
Catherine Ann Sugar is an American biostatistician at the University of California, Los Angeles, where she is Professor in Residence in the Departments of Biostatistics, Statistics and Psychiatry and director of the biostatistics core for the Semel Institute for Neuroscience and Human Behavior. Her research concerns cluster analysis, covariance, and the applications of statistics in medicine and psychiatry.
Francesca Dominici is a Harvard Professor who develops methodology in causal inference and data science and led research projects that combine big data with health policy and climate change. She is a professor of biostatistics, co-director of the Harvard Data Science Initiative, and a former senior associate dean for research in the Harvard T.H. Chan School of Public Health.
Elizaveta (Liza) Levina is a Russian and American mathematical statistician. She is the Vijay Nair Collegiate Professor of Statistics at the University of Michigan, and is known for her work in high-dimensional statistics, including covariance estimation, graphical models, statistical network analysis, and nonparametric statistics.
The National Institute of Statistical Sciences (NISS) is an American institute that researches statistical science and quantitative analysis.
Huixia Judy Wang is a statistician who works as a professor of statistics at George Washington University. Topics in her research include quantile regression and the application of biostatistics to cancer.
Cynthia Diane Rudin is an American computer scientist and statistician specializing in machine learning and known for her work in interpretable machine learning. She is the director of the Interpretable Machine Learning Lab at Duke University, where she is a professor of computer science, electrical and computer engineering, statistical science, and biostatistics and bioinformatics. In 2022, she won the Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity from the Association for the Advancement of Artificial Intelligence (AAAI) for her work on the importance of transparency for AI systems in high-risk domains.
Tze Leung Lai was a Chinese-American statistician of Hong Kong descent. He was the Ray Lyman Wilbur Professor of Statistics, as well as a professor of Biomedical Data Science and of the Institute of Computational and Mathematical Engineering (ICME) at Stanford University. He co-directed the Center for Innovative Study Design (CISD) at the Stanford University School of Medicine. He was the recipient of the COPSS Presidents' Award, one of the highest honors in statistics, in 1983.
Yingying Fan is a Chinese-American statistician and Centennial Chair in Business Administration and Professor in Data Sciences and Operations Department of the Marshall School of Business at the University of Southern California. She is currently the Associate Dean for the PhD Program at USC Marshall. She also holds joint appointments at the USC Dana and David Dornsife College of Letters, Arts and Sciences, and Keck Medicine of USC. Her contributions to statistics and data science were recognized by the Royal Statistical Society Guy Medal in Bronze in 2017 and the Institute of Mathematical Statistics Medallion Lecture in 2023. She was elected Fellow of American Statistical Association in 2019 and Fellow of Institute of Mathematical Statistics "for seminal contributions to high-dimensional inference, variable selection, classification, networks, and nonparametric methodology, particularly in the field of financial econometrics, and for conscientious professional service" in 2020.
Galit Shmueli is a data scientist who works in Taiwan as Tsing Hua Distinguished Professor at the Institute of Service Science, National Tsing Hua University. She is the author of many textbooks in business statistics and is known for her work on information quality, and on clarifying the difference between explanations and predictions in statistical analyses.
