I am enthused by the area of causal inference and machine learning, and my research is at the intersection of economic theory, statistics, and machine learning in the health policy space. I am currently working on developing tree and forest-based methods for learning optimal treatment assignment rules in a multiple treatment arm setting. My thesis work was on proposing and testing heterogeneous effect sub-groups using observational data in conjunction with experimental data.
Another strand of research I am pursuing involves using matching methods to study race-ethnic disparities in education settings.
For details on my research, please refer to my CV.