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Mykel Kochenderfer
Associate Professor of Aeronautics and Astronautics 
Stanford University

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“Automated Decision Making for Safety Critical Applications”
Παρασκευή 6 Ιουνίου 2025 και ώρα 15:00
Αμφιθέατρο Θέλμα Μαυρίδου

Abstract:
Building robust decision making systems for autonomous systems is challenging. Decisions must be made based on imperfect information about the environment and with uncertainty about how the environment will evolve. In addition, these systems must carefully balance safety with other considerations, such as operational efficiency. Typically, the space of edge cases is vast, placing a large burden on human designers to anticipate problem scenarios and develop ways to resolve them. This talk discusses major challenges associated with ensuring computational tractability and establishing trust that our systems will behave correctly when deployed in the real world. We will outline some methodologies for addressing these challenges and point to some research applications that can serve as inspiration for building safer systems.
 

Bio:
Mykel Kochenderfer is Associate Professor of Aeronautics and Astronautics and Associate Professor, by courtesy, of Computer Science at Stanford University and senior fellow at HAI. He is the director of the Stanford Intelligent Systems Laboratory (SISL), conducting research on advanced algorithms and analytical methods for the design of robust decision making systems. Of particular interest are systems for air traffic control, unmanned aircraft, and automated driving where decisions must be made in uncertain, dynamic environments while maintaining safety and efficiency. Research at SISL focuses on efficient computational methods for deriving optimal decision strategies from high-dimensional, probabilistic problem representations.
Prior to joining the faculty in 2013, he was at MIT Lincoln Laboratory where he worked on airspace modeling and aircraft collision avoidance. He received his Ph.D. from the University of Edinburgh in 2006 where he studied at the Institute of Perception, Action and Behaviour in the School of Informatics. He received B.S. and M.S. degrees in computer science from Stanford University in 2003. Prof. Kochenderfer is a co-director of the Center for AI Safety. He is affiliated with the Stanford Artificial Intelligence Laboratory (SAIL), the Human-Centered AI (HAI) Institute, the Symbolic Systems Program, the Bio-X Institute, and Wu Tsai Neurosciences Institute. In 2017, he was awarded the DARPA Young Faculty Award. He is an editor-in-chief of the Journal of Artificial Intelligence Research and an associate editor of the Journal of Aerospace Information Systems. He is an author of the textbooks Decision Making under Uncertainty: Theory and Application (MIT Press, 2015), Algorithms for Optimization (MIT Press, 2019), Algorithms for Decision Making (MIT Press, 2022), and Algorithms for Validation (MIT Press, forthcoming).