John Thickstun

John Thickstun is an assistant professor of computer science. He works on machine learning and generative models. Thickstun is interested in methods that control the behavior of models, both from the perspective of a user who hopes to use a model to accomplish concrete tasks, and from the perspective of a model provider or policymaker who hopes to broadly regulate the outputs of a model. He is also interested in applications of generative models that push beyond the standard text and image modalities, including music technologies.

Previously, Thickstun was a postdoctoral scholar at Stanford University, advised by Percy Liang. He completed his Ph.D. in the Allen School of Computer Science & Engineering at the University of Washington, where he was co-advised by Sham Kakade and Zaid Harchaoui. He studied applied mathematics as an undergraduate at Brown University, advised by Eugene Charniak and Björn Sandstede.