Data Science Institute

Corwin Zigler is Professor of Biostatistics at the Brown University School of Public Health.  His research focuses on quantitative methodology for evaluating the health impacts of environmental and climate-related exposures. His work integrates statistical methodology, epidemiology, large-scale computation, and atmospheric science towards better understanding of how environmental and climate policies impact human health.  His statistical methods expertise covers causal inference in complex obervational settings, with particular focus on Bayesian methods, spatial and network data, and analysis of air pollution. His research has been funded by the National Institutes of Health, the Health Effects Institute, and the U.S. Environmental Protection Agency, and he has served on multiple specialty panels for the U.S. EPA Clean Air Scientific Advisory Committee.

Before arriving at Brown in 2024, Dr. Zigler served as faculty in the Department of Statistics and Data Sciences at the Unviersity of Texas at Austin and in the Department of Biostatistics at the Harvard T.H. Chan School of Public Health.  He completed his Ph.D. in Biostatistics at the University of California, Los Angeles in 2010. 

How does your research, teaching, or other work relate to data or computational science?

I focus mostly on statistical and machine learning methods for causal inference in the environmental sciences. I have successfully collaborated with other quantitative scientists across engineering and other computational disciplines.