Department of Biostatistics
Harvard T.H. Chan School of Public Health
The primary aim of my research is to develop statistical methods that enable maximally rigorous and impactful uses of data to answer environmental health questions. In particular, my recent work centers on the following topics:
(1) Methods for estimation of the health impacts of complex, nationwide environmental regulations
(2) Integration of causal inference principles and methods into epidemiological cancer cluster analyses
(3) New causal inference approaches for studying the effects of environmental exposures on childhood cancer
(4) Methods for studying the impacts of climate, heat, and natural disasters on health and predicting the health impacts of future extreme climate events
Beyond causal inference, my methodological research interests include machine learning, Bayesian methods, latent variable models, spatial statistics, and time series analysis. I have applied these methods to investigate scientific questions not only in environmental health contexts but also in reproductive epidemiology, neuroimaging, social science, and cell biology.