Assistant Professor of Biostatistics
My research focuses on development of Bayesian methods for causal inference in complex observational studies. Specific areas of statistical methods development include methods for causal inference with interference, intermediate variables (mediation analysis, principal stratification), confounding in high dimensions, model uncertainty/model averaging, treatment effect heterogeneity, spatial statistics, missing data, environmental health data science, and tools for transparent/reproducible research.
Most of my research is motivated by problems in public health and epidemiology. Key areas of focus are evaluation of environmental health policies and comparative effectiveness of clinical therapies using large administrative data, but I have worked in a wide range of problems in public health and biomedical science.