Speaker: Assistant Professor Christoforos Mavrogiannis, University of Michigan
Time: 2:40 p.m.-3:30 p.m.
Abstract: Robots have the potential to enhance human productivity by taking over tedious and laborious tasks across important domains like fulfilment, manufacturing, and healthcare. These domains are highly dynamic and unstructured, requiring robots to operate close to users who are occupied with demanding and possibly safety-critical tasks. This level of complexity is challenging for existing systems which largely treat users as moving obstacles. Such systems often fail to adapt to the dynamic context, producing behaviors that distract human activity and hinder productivity. In this talk, I will share insights from my work on robot navigation in crowds, highlighting how mathematical abstractions grounded on our understanding of pedestrian navigation may empower simple models and interpretable architectures to produce safe, efficient, and positively perceived robot motion under close interaction settings. I will close with field-deployment challenges, emphasizing the importance of handling autonomy failures and scaling performance across diverse environments.
Bio: ChristoforosMavrogiannis is an incoming Assistant Professor of Robotics at the University of Michigan and a postdoc at the University of Washington, working on human-robot collaboration and multiagent systems. He has been recognized as an outstanding young scientist by the Heidelberg Laureate Forum, a best-paper finalist at the HRI conference, and a Pioneer at the HRI and RSS conferences. He has been a Hackaday Prize finalist and a winner of the Robotdalen International Innovation Award for his open-source initiative OpenBionics, and currently serves as a mentor for MuSHR, the open-source racecar project of the University of Washington. Christoforos holds a Ph.D. from Cornell University and a Diploma from the National Technical University of Athens.