Maya Petersen

Job title: 
BIDS Faculty Affiliate
Epidemiology and Biostatistics, Public Health, Computational Social Science, Computational Precision Health, Center for Targeted Machine Learning and Causal Inference
  • Professor, Epidemiology and Biostatistics, Berkeley Public Health
  • Co-Director, Berkeley Computational Social Science Training Program (NIH)
  • Co-Director, Joint Program in Computational Precision Health
  • Co-Director, Center for Targeted Machine Learning and Causal Inference
Maya 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, and study design and analytic strategies for impact evaluation. Dr. Petersen’s applied work focuses on developing and evaluating improved HIV prevention and care strategies in resource-limited settings.

Website, Research GateGoogle Scholar

Research interests: 

Causal Inference, Global Health, HIV, Implementation Science, Semiparametric / Nonparametric Statistics