Autonomous Systems in the Intersection of Control, Learning, and Formal Methods

This lecture explores the intersection of control, learning, and formal methods in developing trustworthy autonomous systems. Join Professor Ufuk Topcu from the University of Texas, Austin as he discusses how hybrid solutions across disciplines can overcome challenges in autonomous system design. Discover novel approaches for integrating physics-based, contextual, and structural prior knowledge into data-driven learning algorithms for sequential decision-making processes. Learn how these interdisciplinary methods dramatically improve data efficiency and enable systems to generalize to previously unexperienced environments and tasks. The presentation concludes with insights into promising future research directions in this rapidly evolving field. Presented at Georgia Tech Research's Klaus Computing Building on February 19, 2025, this hour-long talk demonstrates why breaking down disciplinary boundaries is essential for advancing autonomous systems technology.