Teaching

UMich NA/EECS 568, ROB 530: Mobile Robotics: Methods and Algorithms (Prospective)

Joint Instructor, Graduate Course, University of Michigan, 2024

Theory and application of probabilistic and geometric techniques for autonomous mobile robotics. This course presents and critically examines contemporary algorithms for robot perception. Topics include Bayesian filtering; stochastic representations of the environment; motion and sensor models for mobile robots; algorithms for mapping and localization; application to autonomous marine, ground, and air vehicles.

UMich NA 565, ROB 535, ME 599: Self-Driving Cars: Perception and Control

Joint Instructor, Graduate Course, University of Michigan, 2023

Self-driving cars are a transformative technology for society. This course covers the underlying technologies in perception and control. Topics include deep learning, computer vision, sensor fusion, localization, trajectory optimization, obstacle avoidance, and vehicle dynamics. The course includes theoretical underpinnings of self-driving car algorithms and practical application of the material in hands-on labs.