Maya L. Petersen, MD, PhD
- Co-Director, Joint Program in Computational Precision Health
- Co-Director, Center for Targeted Machine Learning and Causal Inference
Biography
Dr. Maya L. Petersen is Professor of Biostatistics and Epidemiology at the University of California, Berkeley. Dr. Petersen’s methodological research focuses on the development and application of novel causal inference methods to problems in health, with an emphasis on longitudinal data and adaptive treatment strategies (dynamic regimes), machine learning methods, adaptive designs, and study design and analytic strategies for cluster randomized trials. She is a Founding Editor of the Journal of Causal Inference and serves on the editorial board of Epidemiology.
Dr. Petersen’s applied work focuses on developing and evaluating improved HIV prevention and care strategies. She currently serves as co-PI (with Dr. Diane Havlir and Dr. Moses Kamya) for the Sustainable East Africa Research in Community Health consortium, and as co-PI (with Dr. Elvin Geng) for the ADAPT-R study (a sequential multiple assignment randomized trial of behavioral interventions to optimize retention in HIV care).
Research Interests
- Causal inference
- Dynamic treatment regimes
- HIV
- Antiretroviral resistance
- Impact evaluation
- Implementation science
Education
- MD – University of California, San Francisco, 2007–2009
-
PhD – Biostatistics
University of California, Berkeley, 2004–2007 - Pre-Doctoral Fellow – Howard Hughes Medical Institute, 2001–2006
-
MS – Health and Medical Sciences
University of California, Berkeley Joint Medical Program, 1999–2002 -
BA – Human Biology
Stanford University, 1994–1998
Publications
Courses Taught
-
- Spring | PB HLTH 252D
- Introduction to Causal Inference
- (“Causal I”)
- Fall | PB HLTH 252E
- Advanced Topics in Causal Inference
- (“Causal II”)
- PB HLTH 290
- Causal Inference Seminar
- (Every two years)
- Doctoral Seminar in Epidemiology
- (First-year students)