I am interested in ensuring the safe operation of robotic systems in the human space.

My work combines safety analysis from control theory with machine learning and artificial intelligence techniques to enable robotic systems to reason competently about their own safety in spite of using inevitably fallible models of the world and other agents. We do this by having robots monitor their own ability to understand the world around them, accounting for how the gap between their models and reality affects their ability to guarantee safety.

Much of my research uses dynamic game theory together with insights from cognitive science to enable robots to strategically plan their interaction with human beings in contexts ranging from human-robot teamwork to drone navigation and autonomous driving. My lab’s scope spans theoretical work, algorithm design, and implementation on a variety of robotic platforms.