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.
|Apr 30, 2021||Defended my PhD in statistics!|
|Feb 17, 2021||Package multChernoff computes finite-sample tail bounds of multinomial LRT.|
|Dec 3, 2020||Package InvariantCausal.jl upgraded to Julia 1.x.|
|Oct 19, 2020||Article with Ema on optimal set-identification of causal effects.|
|Aug 10, 2020||New preprint with Ema on efficient causal estimation under linearity.|
|Aug 4, 2020||Non-nested (causal) model selection paper appears on Biometrika.|
|Jul 5, 2020||Teaching undergraduate probability I and II this summer.|
|May 15, 2020||Presenting my work with Ema at the UW statistics seminar.|