About Me

I am a Ph.D. candidate in Statistics at Stanford University, where I am fortunate to be advised by Professors John Duchi and Scott Linderman. My research is focused on building robust, reliable, and trustworthy artificial intelligence systems with applications in neuroscience. I develop methods to make machine learning models robust to shifts in distribution using synthetic data and Bayesian statistics. Although this work has myriad applications—in areas ranging from cancer screening to language generation—the driving goal is to improve our understanding of the behaviors of brains under uncertainty. This extends to humans with brain-computer interfaces learnign to speak again and to large language models learning in-context. Previously, I have studied in computational physics and molecular dynamics labs, worked at combining AI with cybersecurity at Darktrace—applying Bayesian statistics to network security—and served as the first STEM concentrator to be the editor-in-chief of the Brown Political Review. Outside of research, I used to say I enjoy playing hockey (formerly at the intramural, club, and varsity level at Brown), competing in triathlons, and reading depressing novels, but since coming to Stanford my free time has mostly been spent either playing tennis or trying to keep up with my ever growing Feedly and Anki. I strongly identify as an optimizer (both in terms of past research interests and way of existing) and as such am enamoured with the work of 80000 Hours and Giving What We Can.

I am always happy to chat about research, statistics, or anything else. If you are ever around Stanford, I'd love to grab a coffee or hit a couple rallies.

Contact

Email: first initial lastname at stanford dot edu.
Office: Computing and Data Science, Room E264
Links: GitHub / Goodreads / LinkedIn / Substack