Maya Rossin-Slater is an Associate Professor of Health Policy at Stanford University School of Medicine. She is also a Senior Fellow at the Stanford Institute for Economic and Policy Research (SIEPR), a Research Associate at the National Bureau of Economic Research (NBER) and a Research Fellow at the Institute of Labor Economics (IZA). She received her PhD in Economics from Columbia University in 2013, and was an Assistant Professor of Economics at the University of California, Santa Barbara from 2013 to 2017, prior to coming to Stanford. Rossin-Slater’s research includes work in health, public, and labor economics. She focuses on issues in maternal and child well-being, family structure and behavior, and policies targeting disadvantaged populations in the United States and other developed countries.

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. 

Jeremy Goldhaber-Fiebert, PhD, is a Professor of Health Policy, a Core Faculty Member at the Center for Health Policy and the Department of Health Policy, and a Faculty Affiliate of the Stanford Center on Longevity and Stanford Center for International Development. His research focuses on complex policy decisions surrounding the prevention and management of increasingly common, chronic diseases and the life course impact of exposure to their risk factors. In the context of both developing and developed countries including the US, India, China, and South Africa, he has examined chronic conditions including type 2 diabetes and cardiovascular diseases, human papillomavirus and cervical cancer, tuberculosis, and hepatitis C and on risk factors including smoking, physical activity, obesity, malnutrition, and other diseases themselves. He combines simulation modeling methods and cost-effectiveness analyses with econometric approaches and behavioral economic studies to address these issues. Dr. Goldhaber-Fiebert graduated magna cum laude from Harvard College in 1997, with an A.B. in the History and Literature of America. After working as a software engineer and consultant, he conducted a year-long public health research program in Costa Rica with his wife in 2001. Winner of the Lee B. Lusted Prize for Outstanding Student Research from the Society for Medical Decision Making in 2006 and in 2008, he completed his PhD in Health Policy concentrating in Decision Science at Harvard University in 2008. He was elected as a Trustee of the Society for Medical Decision Making in 2011.

Past and current research topics:

1. Type 2 diabetes and cardiovascular risk factors: Randomized and observational studies in Costa Rica examining the impact of community-based lifestyle interventions and the relationship of gender, risk factors, and care utilization.
2. Cervical cancer: Model-based cost-effectiveness analyses and costing methods studies that examine policy issues relating to cervical cancer screening and human papillomavirus vaccination in countries including the United States, Brazil, India, Kenya, Peru, South Africa, Tanzania, and Thailand.
3. Measles, haemophilus influenzae type b, and other childhood infectious diseases: Longitudinal regression analyses of country-level data from middle and upper income countries that examine the link between vaccination, sustained reductions in mortality, and evidence of herd immunity.
4. Patient adherence: Studies in both developing and developed countries of the costs and effectiveness of measures to increase successful adherence. Adherence to cervical cancer screening as well as to disease management programs targeting depression and obesity is examined from both a decision-analytic and a behavioral economics perspective.
5. Simulation modeling methods: Research examining model calibration and validation, the appropriate representation of uncertainty in projected outcomes, the use of models to examine plausible counterfactuals at the biological and epidemiological level, and the reflection of population and spatial heterogeneity.