James M. Robins is an epidemiologist and biostatistician best known for advancing methods for drawing causal inferences from complex observational studies and randomized trials,particularly those in which the treatment varies with time. He is the 2013 recipient of the Nathan Mantel Award for lifetime achievement in statistics and epidemiology,and a recipient of the 2022 Rousseeuw Prize in Statistics,jointly with Miguel Hernán,Eric Tchetgen-Tchetgen,Andrea Rotnitzky and Thomas Richardson.
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. He also contributed to the development of S.
Mark Johannes van der Laan is the Jiann-Ping Hsu/Karl E. Peace Professor of Biostatistics and Statistics at the University of California,Berkeley. He has made contributions to survival analysis,semiparametric statistics,multiple testing,and causal inference. He also developed the targeted maximum likelihood estimation methodology. He is a founding editor of the Journal of Causal Inference.
Heidi Williams is a Professor of Economics at Dartmouth College and Director of Science Policy at the Institute for Progress. She is a graduate of Dartmouth College,and earned her MSc in development economics from Oxford University and her PhD in Economics from Harvard University. Prior to Dartmouth,Williams was the Charles R. Schwab Professor of Economics at Stanford University and an associate professor at the Massachusetts Institute of Technology. She is a member of the National Bureau of Economic Research.
Elizabeth A. Stuart is a professor of mental health,biostatistics,and health policy and management in the Johns Hopkins Bloomberg School of Public Health. Her research involves causal inference and missing data in the statistics of mental health. She was a co-author on a study showing that post-suicide-attempt counseling can significantly reduce the risk of future suicide.
Miguel Hernán is a Spanish–American epidemiologist. He is the Director of the CAUSALab,Kolokotrones Professor of Biostatistics and Epidemiology at the Harvard T.H. Chan School of Public Health,and Member of the Faculty at the Harvard–MIT Program in Health Sciences and Technology.
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 D. Elashoff is a retired American statistician,formerly the director of biostatistics for Cedars-Sinai Medical Center and professor of biomathematics at UCLA.
Sharon-Lise Teresa Normand is a Canadian biostatistician whose research centers on the evaluation of the quality of care provided by physicians and hospitals,and on the health outcomes for medical devices and medical procedures. She is a professor in the Department of Health Care Policy at the Harvard Medical School and in the Department of Biostatistics at the Harvard T.H. Chan School of Public Health.
Daniela M. Witten is an American biostatistician. She is a professor and the Dorothy Gilford Endowed Chair of Mathematical Statistics at the University of Washington. Her research investigates the use of machine learning to understand high-dimensional data.
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.
Allison Walsh Kurian is an American medical oncologist. She is a Professor of Medicine and Epidemiology &Population Health at Stanford University and an oncologist at the Stanford Cancer Institute.
Rebecca Allana Hubbard is an American biostatistician whose research interests include observational studies and the use of electronic health record data in public health analysis and decision-making,accounting for the errors in this type of data. She is a professor of biostatistics in the Perelman School of Medicine at the University of Pennsylvania.
Donna Spiegelman is a biostatistician and epidemiologist who works at the interface between the two fields as a methodologist,applying statistical solutions to address potential biases in epidemiologic studies.
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.
Mary Elizabeth Landrum is a British-American statistician specializing in biostatistics,examining health services and the quality of health care delivery. She is a professor in the Department of Health Care Policy of the Harvard Medical School.
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.
Layla Mosama Parast Bartroff is an American biostatistician whose research involves surrogate markers,predictive modelling,survival analysis,causal inference,and health care quality. Formerly a senior statistician and co-director of the Center for Causal Inference at the RAND Corporation,she is an associate professor of statistics and data sciences at the University of Texas at Austin. She is also a frequent newspaper and news magazine editorial writer on issues related to public health,supported as a Public Voices Fellow of The OpEd Project.
Lu Wang is a Chinese-American biostatistician whose research topics have included causal inference,dynamic decision-making for medical treatments,missing data,and environmental health. She has also studied the correlation between mercury from seafood and autoimmune disease,and the benefits of providing improved transportation services for healthcare,as a member of the Michigan Institute for Healthcare Policy &Innovation. She is a professor of biostatistics and associate chair for research in biostatistics in the University of Michigan School of Public Health.
