Caleb Chang

Hi! I’m a Robotics Ph.D. student in the Control & Trustworthy Robotics Lab at the University of Washington, advised by Professor Karen Leung.

My research sits at the intersection of control theory, machine learning, and human–robot interaction. I focus on developing personalized, safe, and trustworthy methods for interactive autonomy that move beyond simple collision avoidance. I aim to equip robots with a deeper understanding of human and task context, ensuring their behavior aligns seamlessly with human intent and preferences.

Previously, I received an M.S. in Robotics and a B.S. in Electrical Engineering from Georgia Tech. During my Master’s, I conducted research on imitation learning for robot safety with Professor Matthew Gombolay. As an undergraduate, I focused on perception and planning for manipulators and autonomous vehicles with Professor Patricio Vela. I also worked on safety-critical control with Professor John Dolan at Carnegie Mellon’s Robotics Institute.