- Inference on Gaussian mixture models with dependent labels
- Method-of-Moments Inference for GLMs and Doubly Robust Functionals under Proportional Asymptotics
- Nuisance Function Tuning and Sample Splitting for Optimal Doubly Robust Estimation
- PC Adjusted Testing for Low-Dimensional Parameters
Research Experience
Previously, an Assistant Professor in the Division of Biostatistics at UC Berkeley and a Stein Fellow in the Department of Statistics at Stanford University.
Education
PhD in Biostatistics from Harvard University, advised by Prof. Xihong Lin.
Background
Associate Professor in the Department of Biostatistics at Harvard T.H. Chan School of Public Health. Research interests include understanding broad aspects of causal inference in observational studies, particularly in modern data settings, with a focus on the statistical analysis of environmental mixtures and their effects on cognitive development in children and cognitive decline in aging populations. His research is also motivated by applications in large-scale genetic association studies, developing statistical methods to quantify the effects of climate change on human health, and understanding the effects of homelessness on human health.