is a Ph.D. candidate in Computer Science at Stanford University, co-advised by Professors Dan Jurafsky and James Zou, and a J.D. candidate at Stanford Law School. His research examines the capabilities and limitations of modern language models, focusing on reasoning, hallucination detection and mitigation, and societal applications. He also conducts legal scholarship on constitutional law, administrative law, and AI governance and regulatory policy, and works closely with Professor Daniel E. Ho at the Stanford RegLab. He graduated from Harvard College with a joint degree in Mathematics and Computer Science and a secondary field in Folklore & Mythology, receiving the Thomas T. Hoopes Prize for his undergraduate thesis. His work has appeared in leading venues including Nature Machine Intelligence, The Lancet Digital Health, Journal of Legal Analysis, Journal of Empirical Legal Studies, ACL, EMNLP, ICLR, and NeurIPS. He has worked at Google Brain, Microsoft Research, Meta’s GenAI/Llama team, and OpenEvidence, and has served as a legal intern at the Administrative Conference of the United States and as a litigation summer associate at WilmerHale. His graduate studies have been supported by the Google Ph.D. Fellowship, Stanford HAI-SAP Fellowship, and Stanford Law School Fellowship.
Mirac Suzgun
