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The Board of Veterans Appeals (BVA) adjudicates a high volume of cases and is prone to legal error as a result. We present work from an interdisciplinary collaboration between Stanford’s RegLab and Carnegie Mellon’s Language Technologies Institute to develop a decision support system using natural language processing from a large corpus of BVA decisions.
|Daniel E. Ho
Professor of Law, Stanford Law School
Daniel E. Ho is the William Benjamin Scott and Luna M. Scott Professor of Law at Stanford Law School, Professor of Political Science, Senior Fellow at the Stanford Institute for Economic Policy Research, Associate Director for the Stanford Institute for Human-Centered Artificial Intelligence (HAI), and Director of the Regulation, Evaluation, and Governance Lab (RegLab). (Full bio).
Adjunct Professor, Language Technologies Institute, Carnegie Mellon University
Matthias Grabmair is also a Legal Data Scientist at SINC, one of Germany’s leading research groups in legal informatics, and mentors Master of Computational Data Science (MCDS) Capstone Projects at Carnegie Mellon University’s Language Technologies Institute as adjunct faculty, where he previously taught and conducted research as a Systems Scientist. His research focus is legal informatics, legal data analytics, and natural language processing of legal text. (Full bio).