I am a Predoctoral Research Fellow at Opportunity Insights at Harvard University. I am interested in incorporating machine learning into causal inference, and in studying when the identifying assumptions behind econometric methods hold and when they break down.

My current project uses workforce training programs to assess when observational data can substitute for a randomized trial. Drawing on tax, Census, and external data sources that cover the entire US population, we use debiased machine learning and nuisance estimation to recover the counterfactuals that identify program effects.

I graduated from Brown University with degrees in Applied Mathematics-Economics and Computer Science.