I am a fifth-year PhD student in Stanford's Electrical Engineering department. I'm advised by Mohsen Bayati in the Graduate School of Business. I graduated summa cum laude from Harvard in 2012 with a A.M. in physics, and a A.B. in physics and mathematics.
My primary research interests center around (a) optimizing service operations by developing novel data-driven statistical decision-making tools using techniques from machine learning, and (b) designing improved performance-based contracts using detailed outcomes data on strategic firms and workers. I'm particularly interested in healthcare applications where cost and quality pose serious concerns, and the growing availability of staff and patient data offers an opportunity to significantly improve outcomes through data-driven methods. I find this research particularly exciting as it exposes me to a wide range of techniques, including sequential decision-making, high-dimensional statistics, modeling, and econometrics.
I am on the job market this year!
INFORMS: I will be presenting my job market paper "Online Decision-Making with High-Dimensional Covariates" in the Sunday 4:30-6pm session of the MSOM/Healthcare track. I will also give similar talks in the Nicholson (Sunday 8-9:30am), MSOM (Sunday 11-12:30pm), Pierskalla (Sunday 4:30-6pm) and Service Science (Tuesday 8-9:30am) student paper competition sessions. If you're interested in hearing about my empirical work, I'll be presenting on "Evidence of Upcoding in Pay-for-Performance Programs" in a Monday 1:30-3pm session.