Please join us for the first talk in a special series in the UW Data Science Seminar featuring the AI@UW Seed Grant awardees. The AI@UW Seed Grant projects partner domain researchers from an applied disciplinary field with researchers specializing in AI theory and/or methodology. These projects were supported by the eScience Institute in collaboration with the Office of Research, the Paul G. Allen School of Computer Science & Engineering, the Information School, and the NSF Institute for Foundations of Data Science (IFDS). This seminar will feature UW Computer Science and Engineering PhD students Avi Bose and Daphne Chen, as well as UW Aeronautics and Astronautics Assistant Professor Karen Leung on Thursday, January 30th from 4:30 to 5:20 p.m. PT.
The seminar will be held in Hitchcock Hall 132 – Campus Map.
“Trustworthy Human-AI Shared Autonomy: Theory and Modeling”
Abstract Human-AI interactions are becoming increasingly prevalent in our daily existence, from navigating our roads and sky, assisting in households and warehouses, conducting daring search and rescue missions, and even exploring the frontiers of space. Yet building AI systems that can seamlessly interact and adapt to diverse human users remains an elusive task. In this talk, we will share recent work that studies the theory and models for enabling trustworthy human-AI shared autonomy, from characterizing the performance of offline learning algorithms when deployed on new tasks, efficiently training robot algorithms that can coordinate with human agents, and interpreting multi-agent interactions via the lens of responsibility.
Biography: Avi Bose is a 3rd year PhD student at Paul G.Allen School of Computer Science and Engineering at the University of Washington, coadvised by Prof. Maryam Fazel and Prof. Lillian Ratliff. He is very fortunate to work in close collaboration with Prof. Simon S. Du as well. As of Sep. 2024, he is a visiting researcher at Fair Labs, Meta, working with Lin Xiao.
Daphne Chen is a PhD student in the Department of Computer Science and Engineering at the University of Washington. Her research interests are in enabling intelligent agents to seamlessly learn from humans. She has received an MS in Robotics from Carnegie Mellon University and a BS from Georgia Institute of Technology.
Karen Leung is an Assistant Professor and the Vagners & Christianson Endowed Faculty Fellow in Aeronautics & Astronautics at the University of Washington. She directs the Control and Trustworthy Robotics Lab (CTRL) which focuses on developing safe, intelligent, and trustworthy autonomous systems that can operate seamlessly with, alongside, and around humans. Before joining UW, Karen was a research scientist at NVIDIA, working in the Autonomous Vehicle Research Group, where she currently holds a partial appointment. Karen received her M.S. and Ph.D. in Aeronautics and Astronautics from Stanford University, and a combined B.S./B.E. in Mathematics and Aerospace Engineering from the University of Sydney, Australia. She is a recipient of the UW + Amazon Science Hub Faculty Research Award and received the William F. Ballhaus Prize for Best Ph.D. Thesis Award.
The UW Data Science Seminar is an annual lecture series at the University of Washington that hosts scholars working across applied areas of data science, such as the sciences, engineering, humanities and arts along with methodological areas in data science, such as computer science, applied math and statistics. Our presenters come from all domain fields and include occasional external speakers from regional partners, governmental agencies and industry.
The 2024-2025 seminars will be held in person, and are free and open to the public.