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Austin Peters is a Harry Bigelow Teaching Fellow and Lecturer in Law at the University of Chicago Law School. His research primarily focuses on the application of artificial intelligence, particularly large language models and machine learning, to various topics within civil procedure and statutory interpretation. His scholarship has been published in prominent law reviews including the Northwestern University Law Review and the University of Pennsylvania Law Review, as well as in proceedings for computer science conferences such as DEEM at NeurIPS. Before becoming a Bigelow Fellow, Austin clerked for Judge Kevin C. Newsom on the United States Court of Appeals for the Eleventh Circuit. He holds a PhD and JD in Political Science from Stanford University, alongside a BA in Political Science from the University of California, San Diego, where he graduated magna cum laude with Highest Honors. Throughout his career, Austin has contributed to several academic conferences focusing on empirical legal studies and the intersection of machine learning with legal opinions.
Stanford Law School, Deborah L. Rhode Center for Legal Profession • Stanford, CA
Eleventh Circuit Court of Appeals, Judge Kevin C. Newsom • United States
Palantir Technologies •
American Enterprise Institute, Arthur C. Brooks •
Department of Philosophy