Posts classified under: Faculty

Sherri Rose, Ph.D. is an Associate Professor of Health Policy and Co-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 risk adjustment, ethical algorithms in health care, comparative effectiveness research, 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 coauthored the first book on machine learning for causal inference, with a sequel text released in 2018. She has been Co-Editor-in-Chief of the journal Biostatistics since 2019. Read more about the Health Policy Data Lab.

Our research in the Translational Cancer Evolution Laboratory focuses on the stochastic biological processes underlying cancer evolution with the goal to improve the prognosis and treatment of tumors. We develop computational methods to learn from large-scale biological data sets and design mathematical models to predict patient outcomes, generate novel hypotheses, and explain observations on a mechanistic level. We apply these methods to genomic data from clinically-annotated patient cohorts to advance precision medicine. For example, we have designed methods to optimize cancer early detection strategies and to find optimal combination therapies to minimize the risk of cancer relapse.

My research is focused on understanding the health implications of the myriad decisions that are made by corporations and governments every day — decisions that profoundly shape the social and economic worlds in which we live and work. I analyze population based datasets to demonstrate the health implications of economic and social factors that can give the public and policy makers evidence to support new strategies for promoting health and well-being. In all of his work, I focus on the implications of these exposures for health inequalities. Since often policy and programmatic changes can take decades to influence health, my research also includes more basic research in understanding biological signals that may act as early warning signs of systemic disease, in particular accelerated aging. I examine how social and economic policy changes influence a range of early markers of disease and aging, with a particular recent focus on DNA methylation.

https://profiles.stanford.edu/david-rehkopf

Interests lie at the nexus of physics, biology, and biotechnology. His research is concerned with developing new approaches to biological measurement and applying these approaches to problems of both fundamental and medical interest. Areas of interest include genomic diagnostics, systems biology, microbial ecology, and single cell genomics. Read more about the Quake Lab.

https://profiles.stanford.edu/stephen-quake