Join in MY580 or online (Zoom)

Title and abstract to come.

Speaker bio

Nick Rhinehart is an Assistant Professor at the University of Toronto, where he is appointed to the Institute for Aerospace Science, cross-appointed to the Department of Computer Science, and a faculty member of the Robotics Institute.

He leads the Learning, Embodied Autonomy, and Forecasting (LEAF) lab, which studies learning-based foundations for reliable model-based robot autonomy. The LEAF lab’s recent work focuses on learning transferable dynamics and world models, adapting learned models for efficient real-time planning, and inferring task objectives from sparse human and language-based supervision.

Prof. Rhinehart joined the University of Toronto after holding positions as a Senior Research Scientist at Waymo Research from 2022–2024 and a Postdoctoral Researcher at the UC Berkeley Artificial Intelligence Research laboratory from 2019–2022. He received a Ph.D. in Robotics from Carnegie Mellon University (CMU). His work received the Best Paper Honorable Mention Award at ICCV 2017 and the Best Paper Award at the ICML 2019 Workshop on AI for Autonomous Driving. Prof. Rhinehart holds undergraduate degrees in Engineering and Computer Science from Swarthmore College.