Harvard Catalyst Profiles

University of Pennsylvania	BSc
Harvard TH Chan School of Public Health	MSc
Harvard University	PhD

Barbra Dickerman uses causal inference methods and large health databases to improve health decision-making. This work has helped to inform health decision-making at national and global levels, as well as the design and conduct of comparative effectiveness and safety studies at scale.

Barbra is Assistant Professor of Global Cancer Prevention in the Zhu Family Center for Global Cancer Prevention and Department of Epidemiology at the Harvard T.H. Chan School of Public Health, and a member of the Harvard CAUSALab. She also serves as co-director of the VA-CAUSAL Methods Core, an initiative of the U.S. Veterans Health Administration to integrate high-quality data and explicitly causal methodologies in a nationwide learning health system.

She teaches causal inference methodology at the Harvard Chan School, where she also mentors junior investigators and students. She has developed several CAUSALab courses (on fundamentals of confounding adjustment, advanced confounding adjustment, and target trial emulation) which aim to make causal inference concepts and methods more accessible to a diverse global audience. In Summer 2024, these courses reached participants representing 35+ countries and 180+ organizations, spanning both academia and industry.