Improving Team Performance and Dynamics within Human-Robot Teams
Robots are increasingly joining groups and teams of people to perform collaborative tasks in a variety of settings. For example, robots are helping to perform medical surgeries, aiding police forces in the removal of explosives, and detecting spills in local grocery stores. In order to improve the performance of these human-robot teams, my work focuses on developing robots that shape team dynamics to promote inclusion, trust, and cohesion. Using computational models that detect relevant verbal and nonverbal social cues, predict high-level social dynamics, and generate decision-making policies for robot actions, I explore how a robot’s actions within a group shape human team members’ behavior for the benefit of the team.
Host: Marshini Chetty
Sarah Sebo is an Assistant Professor of Computer Science at the University of Chicago where she directs the UChicago Human-Robot Interaction (HRI) Lab. She received her PhD in Computer Science from Yale University in 2020 and Bachelors in Electrical and Computer Engineering from Franklin W. Olin College of Engineering in 2014.