I am a PhD candidate in statistics. I work on problems related to causal inference. My advisor is Thomas Richardson.
I am generally interested in addressing the statistical challenges posed by causal inference, such as conducting valid inference under non-standard asymptotics, irregularity, weak signal, or even partial identifiability. I am also interested in approaches that enhance efficiency and interpretability, such as empirical Bayes.
Previously, I studied computer science at Duke and MIT.