Today's society is rapidly advancing towards robotics systems that interact and collaborate with humans, e.g., semi-autonomous vehicles interacting with drivers and pedestrians, medical robots used in collaboration with doctors, or service robots interacting with their users in smart homes. In this talk, I will first discuss interactive autonomy, where we develop algorithms for autonomous systems that influence humans, and further leverage these effects for better safety, efficiency, coordination, and estimation. I will then focus on our efficient active learning methods to build predictive models of humans's preferences by eliciting comparisons from a mixed set of humans, and further analyzing the generalizability and robustness of the learned human models for safe and seamless interaction with robots.
The Stanford EE Computer Systems Colloquium (EE380) meets on Wednesdays 4:30-5:45 throughout the academic year. Talks are given before a live audience in Room B03 in the basement of the Gates Computer Science Building on the Stanford Campus. The live talks (and the videos hosted at Stanford and on YouTube) are open to the public.
Stanford students may enroll in EE380 to take the Colloquium as a one unit S/NC class. Enrolled students are required to keep and electronic notebook or journal and to write a short, pithy comment about each of the ten lectures and a short free form evaluation of the class in order to receive credit. Assignments are due at the end of the quarter, on the last day of examinations.
EE380 is a video class. Live attendance is encouraged but not required. We (the organizers) feel that watching the video is not a substitute for being present in the classroom. Questions are encouraged.
Many past EE380 talks are available on YouTube, see the EE380 Playlist.
Dorsa Sadigh is an assistant professor in Computer Science and Electrical Engineering at Stanford University. Her research interests lie in the intersection of robotics, learning and control theory, and algorithmic human-robot interaction. Specifically, she works on developing efficient algorithms for autonomous systems that safely and reliably interact with people. Dorsa has received her doctoral degree in Electrical Engineering and Computer Sciences (EECS) at UC Berkeley in 2017, and has received her bachelor's degree in EECS at UC Berkeley in 2012. She is awarded the NSF and NDSEG graduate research fellowships as well as Leon O. Chua departmental award, Arthur M. Hopkin departmental award.