I received my Ph.D. from in the biostatistics department at UC Berkeley working with Mark van der Laan. Before that, I studied mathematics and worked as a Freeport-McMoRan research fellow at TGen. During my graduate studies, I was fortunate to serve as a BIDS Fellow and Biomedical Big Data Fellow
My research interests revolve around personalized health, causal inference and machine learning. Most of my current work involves causal inference with time and network dependence, optimal individualized treatment, online learning, optimal surrogates, reinforcement learning, and adaptive sequential designs. As a graduate student, I enjoyed numerous collaborations with Bill and Melinda Gates Foundation, Gilead Sciences, Kaiser Permanente, Parexel and TGen. I am also a founding core developer of the tlverse project, software ecosystem for targeted learning.
