Hi, I'm Nick Rhinehart, an Assistant Professor at the University of Toronto.

• Primary Appointment: The Institute for Aerospace Studies.
• Cross Appointment: The Department of Computer Science.
• Faculty Affiliate: The Robotics Institute.

I lead the Learning, Embodied Autonomy, and Forecasting (LEAF) lab. One of our central aims is general-purpose model-based control: autonomous systems that can be directed to perform a wide range of tasks by combining accurate models of the world with learned objectives. Two capabilities are essential to this vision: forecasting, learning to predict future observations and outcomes from rich sensor data, and reward learning, inferring what humans actually want from demonstrations, preferences, and other feedback. Together, these would allow an agent to simulate what will happen under different actions and select behavior aligned with human intent, without requiring hand-designed rewards or task-specific engineering. Our research draws on imitation learning, reinforcement learning, generative modeling, and information theory, with applications spanning autonomous driving, robot navigation, manipulation, and beyond.

I obtained a Ph.D. in Robotics at Carnegie Mellon University with Kris Kitani. Previously, I was a Senior Research Scientist at Waymo Research, and a Postdoctoral Scholar with Sergey Levine in the Berkeley Artificial Intelligence Research group.