My research focuses on causal inference, program evaluation, and econometric methods for credible empirical analysis. I study how tools from econometrics and data science can be used to draw reliable conclusions from observational and administrative data, with applications in economics, health, public policy, and business analytics.

A central theme of my work is the integration of methodological rigor with applied relevance. I develop methods and software that are useful for researchers and decision-makers, with particular interests in regression discontinuity designs, treatment effects, and nonparametric inference.