George Pappas is the UPS Foundation Professor at the Department of Electrical and Systems Engineering at the University of Pennsylvania. He also holds a secondary appointment in the Departments of Computer and Information Sciences, as well as Mechanical Engineering and Applied Mechanics. He currently serves as the Associate Dean for Research and Innovation in the School of Engineering and Applied Science and as the Director of the Raj and Neera Singh program in Artificial Intelligence. Pappas’s research focuses on control systems, robotics, autonomous systems, formal methods, and machine learning for safe and secure cyber-physical systems. He has received numerous awards, including the NSF PECASE, the Antonio Ruberti Young Researcher Prize, the George S. Axelby Award, the O. Hugo Schuck Best Paper Award, and the George H. Heilmeier Faculty Excellence Award. Pappas has mentored more than fifty students and postdocs, now faculty in leading universities worldwide. He is a Fellow of IEEE, IFAC, and was elected to the National Academy of Engineering in 2024.
Research Projects
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In the Press
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Lecture
- Sharp Rates in Dependent Learning Theory: Avoiding Sample Size Deflation for the Square Loss. Ingvar Ziemann, Stephen Tu, George J. Pappas, Nikolai Matni. In Proceedings of the International Conference on Machine Learning, Vienna, Austria. (2024) [PDF] [DOI] [PubMed]
- Conformal Prediction with Learned Features. Shayan Kiyani, George J. Pappas, Hamed Hassani. In Proceedings of the International Conference on Machine Learning, Vienna, Austria (2024) [PDF] [DOI]
- Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples. Thomas Zhang, Bruce D Lee, Ingvar Ziemann, George J. Pappas, Nikolai Matni. In Proceedings of the International Conference on Machine Learning, Vienna, Austria. (2024) [PDF] [PubMed]
- Finite-Time Analysis of Asynchronous Multi-Agent TD Learning. Nicolò Dal Fabbro, Arman Adibi, Aritra Mitra, George J. Pappas. In Proceedings of the 2024 American Control Conference, Toronto. (2024)
- Structural Risk Minimization for Learning Nonlinear Dynamics. Charalampia Stamouli, Evangelos Chatzipantazis, George J. Pappas. In Proceedings of the 2024 American Control Conference, Toronto. (Best Student Paper Award) (2024)