George J. 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, and Mechanical Engineering and Applied Mechanics. Previously, he served as the Deputy Dean for Research in the School of Engineering and Applied Science. Pappas's research interest focus on control systems, robotics and autonomous systems, formal methods, 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, most of the faculty in leading universities around the world. Recognized for his outstanding contributions, Pappas is a Fellow of IEEE, IFAC, and was elected to the National Academy of Engineering in 2024.
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Feb 2024: George J. Pappas to direct first A.I. undergraduate degree in the Ivy League More
Feb 2024: George J. Pappas elected to the U.S. National Academy of Engineering. More
May 2023: Outstanding Multi-Robot Systems Paper at IEEE ICRA More
Oct 2022: Best Paper Award at ACM Transactions on Embedded Computing Systems, More
Dec 2021: Alena Rodionova wins the Best Student Paper Award at IEEE CDC 2021, More
Feb 2021: Distinguished Alumni Award, UC Berkeley EECS, More
July 2020: George J. Pappas will be a semi-plenary speaker at the 2020 IFAC World Congress. More
May 2020: Best Paper Award, IEEE ICASSP, May 2020. More
Apr 2020: George J. Pappas will be a keynote speaker at CPSWEEK 2020. More
January 2020: George J. Pappas will be a plenary speaker at the Chinese Control Conference in Shenyang, China. More
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Selected Recent Publication
Dai, Zhirui, Arash Asgharivaskasi, Thai Duong, Shusen Lin, Maria-Elizabeth Tzes, George Pappas, and Nikolay Atanasov. "Optimal scene graph planning with large language model guidance." arXiv preprint arXiv:2309.09182 (2023).
Chao, Patrick, Alexander Robey, Edgar Dobriban, Hamed Hassani, George J. Pappas, and Eric Wong. "Jailbreaking black box large language models in twenty queries." arXiv preprint arXiv:2310.08419 (2023).
Robey, Alexander, Eric Wong, Hamed Hassani, and George J. Pappas. "Smoothllm: Defending large language models against jailbreaking attacks." arXiv preprint arXiv:2310.03684 (2023).
Ziemann, Ingvar, Anastasios Tsiamis, Bruce Lee, Yassir Jedra, Nikolai Matni, and George J. Pappas. "A Tutorial on the Non-Asymptotic Theory of System Identification." In 2023 62nd IEEE Conference on Decision and Control (CDC), pp. 8921-8939. IEEE, 2023.
A. Tsiamis, I. Ziemann, N. Matni and G. J. Pappas, "Statistical Learning Theory for Control: A Finite-Sample Perspective," in IEEE Control Systems Magazine, vol. 43, no. 6, pp. 67-97, Dec. 2023
L. Lindemann, M. Cleaveland, G. Shim and G. J. Pappas, "Safe Planning in Dynamic Environments Using Conformal Prediction," in IEEE Robotics and Automation Letters, vol. 8, no. 8, pp. 5116-5123, Aug. 2023
M. Fazlyab, M. Morari and G. J. Pappas, Safety Verification and Robustness Analysis of Neural Networks via Quadratic Constraints and Semidefinite Programming, in IEEE Transactions on Automatic Control, vol. 67, no. 1, pp. 1-15, Jan. 2022
[ All Publications ]
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