Peter Henderson is a PhD Student in Computer Science at Stanford University, advised by Dan Jurafsky, and a JD candidate at Stanford Law School. His research centers around machine learning, natural language processing, and causal inference, along with their applications in law and policy. Prior to joining Stanford, he received his M.Sc. from McGill University with a thesis focusing on reproducibility and reusability of deep reinforcement learning methods (advised by Joelle Pineau and David Meger). He also previously worked as a Scientist at Amazon Alexa and a Software Engineer at Amazon Web Services. Peter’s research with the RegLab involves using natural language processing and machine learning to address basic challenges in mass adjudication.