Causality

Biostatistics & Epidemiology - UC Berkeley

Maya Petersen, MD, PhD is Associate Professor of Epidemiology and Biostatistics at the University of California, Berkeley School of Public Health. Dr. Petersen's methodological research focuses on causal inference methods, with an emphasis on longitudinal data, adaptive treatment strategies (dynamic regimes), machine learning, and study design and analysis of cluster randomized trials. Her applied work focuses on developing and evaluating improved HIV prevention and care strategies in resource-limited settings. Maya is currently co-PI (with Diane Havlir and Moses Kamya) of the SEARCH Study, a large HIV prevention and community health study in East Africa, and co-PI (with Elvin Geng) of the AdaPT-R Trial, a sequential multiple assignment randomized trial to develop adaptive strategies that optimize retention in HIV care in Kenya.

Biostatistics - UMass Amherst

Laura B. Balzer, PhD MPhil, is an Assistant Professor of Biostatistics at the University of Massachusetts-Amherst. She earned her PhD from the University of California-Berkeley and completed her post-doctoral studies at the Harvard T.H. Chan School of Public Health. Her areas of expertise include causal inference, machine learning, and dependent data. Dr. Balzer is the Primary Statistician for two cluster randomized trials: the SEARCH study for HIV prevention and treatment in East Africa and the SPIRIT study for TB prevention in Uganda. Her work is supported by the National Institutes of Health (NIH). Dr. Balzer received the ASA’s Causality in Statistics Education Award and the Gertrude M. Cox Scholarship.