Zach Shahn is a statistician and methodologist. His research interests center on the development and application of methods for causal inference, particularly for time-varying interventions. In his applied work, he has studied dynamic treatment strategies in the ICU, monitoring strategies for HIV patients under resource constraints, and impacts of Medicaid expansion.
Dr. Shahn is an Assistant Professor of Biostatistics at the CUNY Graduate School of Public Health and Health Policy. He received a PhD in statistics from Columbia University, was a post-doctoral fellow in the departments of Epidemiology and Biostatistics at the Harvard School of Public Health, and worked at IBM Research prior to joining CUNY.