I’m a joint JD-PhD (Computer Science) candidate at Stanford University where I’m lucky enough to be advised by Dan Jurafsky. I’m also an OpenPhilanthropy AI Fellow and a Graduate Student Fellow at the Regulation, Evaluation, and Governance Lab. At Stanford Law School, I co-led the Domestic Violence Pro Bono Project, worked on client representation with the Three Strikes Project, and contributed to the Stanford Native Law Pro Bono Project. Previously, I was lucky enough to be advised by David Meger and Joelle Pineau for my M.Sc. at McGill University and the Montréal Institute for Learning Algorithms.
I also spent time as a Software Engineer and Applied Scientist at Amazon AWS/Alexa, worked with Justice Cuéllar at the California Supreme Court, am a part-time researcher with the Internal Revenue Service Research, Applied Analytics and Statistics Division, and am a Technical Advisor at the Institute for Security+Technology.
My research focuses on the intersection of AI and Law, in particular creating robust decision-making systems and regulatory frameworks for safe ML deployments. Some of my work has received coverage by TechCrunch, Science, The Wall Street Journal, Bloomberg, and more. I also occassionally post a roundup of all thing AI policy, the latest of which is here. Overall, I’m interested in a wide range of other technical machine learning research, policy, and legal work, so get in touch if you’d like to collaborate!