I am a Postdoctoral Fellow at Stanford Data Science where I work with Guido Imbens. I completed my PhD in Computer Science at UC Berkeley, advised by Avi Feller and Emi Nakamura. My work is at the intersection of Machine Learning, Causal Inference, and Macroeconomics. On the technical side, my recent work has focused on debiased machine learning, sensitivity analysis, and causal issues in reinforcement learning. My applied research studies the interplay between data and structural models for household income and consumption.

In a previous life, I worked in Krste Asanović’s lab, where I built hardware accelerators for gene sequencing and Markov Chain Monte Carlo algorithms. Prior to graduate school, I was a research engineer at Reservoir Labs where I developed tensor decomposition algorithms and applied them to gene expression and computer networks. I received a B.S. in Electrical Engineering and Computer Science from Yale University.