Sherri Rose

Sherri Rose Stanford Health Policy

Sherri Rose, PhD

  • Professor, Health Policy
  • Director, Health Policy Data Science Lab

Encina Commons,
615 Crothers Way
Stanford, CA 94305-6006

 

Biography

Sherri Rose, PhD, is a Professor of Health Policy and Director of the Health Policy Data Science Lab at Stanford University. Her research is centered on developing and integrating innovative statistical machine learning approaches to improve human health and health equity. Within health policy, Dr. Rose works on ethical algorithms in health care, risk adjustment, chronic kidney disease, and health program evaluation. She has published interdisciplinary projects across varied outlets, including Biometrics, Journal of the American Statistical Association, Journal of Health Economics, Health Affairs, and New England Journal of Medicine. In 2011, Dr. Rose co-authored the first book on machine learning for causal inference, with a sequel text released in 2018.

Dr. Rose has been honored with an NIH Director’s Pioneer Award, NIH Director's New Innovator Award, the ISPOR Bernie J. O'Brien New Investigator Award, and multiple mid-career awards, including the Gertrude M. Cox Award. She is a Fellow of the American Statistical Association and received the Mortimer Spiegelman Award, which recognizes the statistician under age 40 who has made the most significant contributions to public health statistics. In 2024, she was recognized with both the ASHEcon Willard G. Manning Memorial Award for Best Research in Health Econometrics and the American Statistical Association Outstanding Statistical Application Award. Her research has been featured in The New York Times, USA Today, and The Boston Globe. She was Co-Editor-in-Chief of the journal Biostatistics from 2019-2023.

She received her PhD in Biostatistics from the University of California, Berkeley and a BS in Statistics from The George Washington University before completing an NSF Mathematical Sciences Postdoctoral Research Fellowship at Johns Hopkins University. 

In The News

Software Developer
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Policy Brief: The Complexities of Race Adjustment in Health Algorithms

As policymakers, health-care practitioners, and technologists pursue the application of AI and machine learning (ML) algorithms in health care, this policy brief underscores the need for health equity research and highlights the limitations of employing technical “fixes” to address deep-seated health inequities.
cover link Policy Brief: The Complexities of Race Adjustment in Health Algorithms
Sherri Rose-JSM Award
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Sherri Rose Honored with ASA Outstanding Statistical Application Award

The annual Outstanding Statistical Application Award recognizes the authors of a paper that demonstrates an outstanding application of statistics in any substantive field.
cover link Sherri Rose Honored with ASA Outstanding Statistical Application Award
Sherri Rose Outdoor Profile cropped
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Sherri Rose Wins ASHEcon Manning Award for Best Research in Health Econometrics

The Willard G. Manning Memorial Award is given for the best published health economics research in econometric methodology or application.
cover link Sherri Rose Wins ASHEcon Manning Award for Best Research in Health Econometrics