I am a Miller fellow at the University of California, Berkeley. I am hosted in the Department of Statistics by Michael I. Jordan.

I completed my PhD in the Department of Statistics and Data Science at Carnegie Mellon University where I was advised by Aaditya Ramdas. Before that, I obtained a Bachelor’s degree in mathematics and statistics from the University of Waterloo.

I am broadly interested in statistics, machine learning theory, and probability. Recently, I have focused on topics in anytime-valid sequential inference, e-values, causal inference, concentration inequalities, and strong limit theorems.