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Bradley Efron is an American statistician. Efron has been president of the American Statistical Association (2004) and of the Institute of Mathematical Statistics (1987–1988). He is a past editor of the Journal of the American Statistical Association, and he is the founding editor of the Annals of Applied Statistics. Efron is also the recipient of many awards.
Statistics is the theory and application of mathematics to the scientific method including hypothesis generation, experimental design, sampling, data collection, data summarization, estimation, prediction and inference from those results to the population from which the experimental sample was drawn. This article lists statisticians who have been instrumental in the development of theoretical and applied statistics.
David Amiel Freedman was Professor of Statistics at the University of California, Berkeley. He was a distinguished mathematical statistician whose wide-ranging research included the analysis of martingale inequalities, Markov processes, de Finetti's theorem, consistency of Bayes estimators, sampling, the bootstrap, and procedures for testing and evaluating models. He published extensively on methods for causal inference and the behavior of standard statistical models under non-standard conditions – for example, how regression models behave when fitted to data from randomized experiments. Freedman also wrote widely on the application—and misapplication—of statistics in the social sciences, including epidemiology, public policy, and law.
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.
Guido Wilhelmus Imbens is a Dutch-American economist whose research concerns econometrics and statistics. He holds the Applied Econometrics Professorship in Economics at the Stanford Graduate School of Business at Stanford University, where he has taught since 2012.
Elizabeth Alison Thompson is a British-born American statistician at the University of Washington. Her research concerns the use of genetic data to infer relationships between individuals and populations. She is the 2017–2018 president of the International Biometric Society.
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.
Janet Dixon Elashoff is a retired American statistician, formerly the director of biostatistics for Cedars-Sinai Medical Center and professor of biomathematics at the University of California, Los Angeles.
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.
Rina Foygel Barber is an American statistician whose research includes works on the Bayesian statistics of graphical models, false discovery rates, and regularization. She is the Louis Block Professor of statistics at the University of Chicago.
Babette Anne Brumback is an American biostatistician known for her work on causal inference. She is a professor of biostatistics at the University of Florida.
Erica Eleanor Margret Moodie is a Canadian biostatistician known for her work on dynamic treatment regimes. She is Canada Research Chair and Professor in the Department of Epidemiology, Biostatistics, and Occupational Health at McGill University.
Sherri Rose is an American biostatistician. She is an associate professor of health care policy at Stanford University, having formally worked at Harvard University. A fellow of the American Statistical Association, she has served as co-editor of Biostatistics since 2019 and Chair of the American Statistical Association’s Biometrics Section. Her research focuses on statistical machine learning for health care policy.
Thomas Lumley is an Australian statistician who serves as the chair of biostatistics at the University of Auckland in New Zealand. Lumley is also a member of the "R Core Team."
Guosheng Yin is a statistician, data scientist, educator and researcher in Biostatistics, Statistics, machine learning, and AI. Presently, Guosheng Yin is Chair in Statistics in Department of Mathematics at Imperial College London. Previously, he served as the Head of Department and the Patrick S C Poon Endowed Chair in Statistics and Actuarial Science, at the University of Hong Kong. Before he joined the University of Hong Kong, Yin worked at the University of Texas M.D. Anderson Cancer Center till 2009 as a tenured Associate Professor of Biostatistics.
Rui Song is a Chinese-American statistician. Her research interests include machine learning, causal inference, and independence screening for variable selection, with applications to precision medicine and economics. She works for Amazon as a senior principal scientist.
Fan Li is a Chinese-American biostatistician whose research includes causal inference and propensity score matching, and their application to comparative effectiveness research in health care. She is a professor in the Duke University Department of Statistical Science, with a secondary appointment in Duke's Department of Biostatistics and Bioinformatics.
Andrea Gloria Rotnitzky is an Argentine biostatistician whose research involves causal inference on the effects of medical interventions in the face of missing data. She is Prentice Endowed Professor of Biostatistics in the University of Washington School of Public Health.
Robert L. Strawderman is an academic biostatistician and researcher who holds the Donald M. Foster, MD Distinguished Professorship in Biostatistics at the University of Rochester. He has served as chair of the Department of Biostatistics and Computational Biology since 2012. Strawderman's principal research interests include semiparametric methods for missing and censored data and statistical learning methods for risk and outcome prediction. Contributions in numerous other areas include inference and variable selection in the areas of dynamic treatment regimes and causal inference in mediation analysis and for recurrent events.
References
- 1 2 3 "Layla Parast", Directory, University of Texas at Austin Department of Statistics and Data Sciences, retrieved 2023-10-15
- 1 2 3 4 5 Layla Parast Aims to Improve Healthcare Using Biostatistics, University of Texas at Austin Department of Statistics and Data Sciences, April 5, 2022, retrieved 2023-10-15
- ↑ Two Cohorts Announced for Prestigious Public Voices Fellowship, University of Texas at Austin Office of the Executive Vice President and Provost, August 10, 2022, retrieved 2023-10-15
- 1 2 "Layla Parast, Jay Bartroff", Weddings, The New York Times , October 23, 2011, retrieved 2023-10-15
- ↑ Parast, Layla Mosama (2012), Landmark Prediction of Survival, Harvard University
- ↑ Layla Parast at the Mathematics Genealogy Project
- 1 2 Robards-Forbes, Esther (January 28, 2022), Meet the Scientists Who are New to the Faculty this Spring, University of Texas at Austin College of Natural Sciences, retrieved 2023-10-15
- ↑ 2023 ASA Fellows (PDF), American Statistical Association, retrieved 2023-10-15
