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 and able to accurately quantify their own uncertainty. Although this work has myriad applications—in areas ranging from cancer screening to language generation—the driving goal is to improve brain-computer interfaces to help people regain the ability to speak. 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 overcome my deficiencies in statistics. As part of this desire to improve my statistical knowledge, I created a Bayesian model to predict pitcher performance for my fantasy baseball league, winning three of the past four seasons (Spencer Strider and Ronald Acuña's frailty really destroyed me one year).

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 on the tennis courts.

Contact

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