I recently completed my PhD in Statistics from University of Washington, Seattle. I work on problems related to causal inference. My PhD advisor is Thomas S. Richardson. My doctoral thesis is on Likelihood analysis of causal models.
I work on statistical foundations of causal inference, including model selection, irregularity and partial identifiability. Recently, I have been working on the efficiency theory of causal graphical models.
|Aug 30, 2022||A new review paper that clarifies misconceptions on confounder selection.|
|May 20, 2022||Attending ACIC 2022 and presenting in Poster Session #1 (May 24 @5pm).|
|Feb 24, 2022||What is the most “efficient” identifying formula for your causal effect? This new preprint answers this question in the context of causal DAGs.|
|Feb 5, 2022||Try simplifying your causal DAG with reduceDAG?|