I am a postdoc at Vertaix and the Computer Science department of Princeton University, working with Prof. Adji Bousso Dieng. I obtained my Ph.D. in Computer Science from McKelvey School of Engineering at Washington University in St. Louis, advised by Prof. Roman Garnett. I was also briefly advised by Prof. Sanmay Das while he was at WashU. My research interests are in Bayesian machine learning, active search, and general decision-making under uncertainty to accelerate and automate scientific discovery.

I am also an avid programmer and a Python enthusiast. Aside from research, I often write about data science, scientific computing, and Python programming.

My CV, last updated in October 2025, can be found here. My research statement can be found here.

Recent news

November 2025: Building on Vendi information gain, we propose a new active learning policy for ecology. It will be presented at the AI2ASE workshop at AAAI 2026. The preprint is available here.

May 2025: The preprint for Vendi information gain is now public.

April 2025: Very honored to have received the Turner dissertation award for my Ph.D. thesis, “Experimental Design for Scientific Discovery.”

January 2025: Our paper on probabilistic modeling of metastable polymorph synthesizability is accepted to the Journal of the American Chemical Society.

October 2024: Our paper on Bayesian optimization for metal–organic frameworks is accepted to Chemical Science.

[Last updated in October 2025]