I am a PhD candidate in Statistics at Stanford University. 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 on 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.