I am a PhD candidate in statistics. I work on problems related to causal inference. My advisor is Thomas Richardson.

I am interested in addressing various statistical challenges posed by causal inference, such as inference under non-standard asymptotics, finite sample, irregularity, and partial identifiability. I am also interested in approaches that enhance efficiency and interpretability, such as Bayes, empirical Bayes and graphical models.

Previously, I studied computer science at Duke and MIT.