Kissing Number Breakthrough: PackingStar AI Advances | AcademicJobs
Peking University and Fudan researchers use PackingStar RL to set new kissing number lower bounds in dimensions 25-31, revolutionizing high-dimensional sphere packing.
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Yaodong Yang is an Assistant Professor (Boya Young Scholar) and Assistant Dean at the Institute for Artificial Intelligence, Peking University. He also serves as Chief Scientist of the PKU–PsiBot Joint Laboratory. His research focuses on reinforcement learning, multi-agent systems, game theory, multi-agent reinforcement learning, game intelligence, and decision-making technologies, with additional emphasis on experience learning and alignment of AI and embodied agents. He completed his undergraduate studies at the University of Science and Technology of China, obtained a master's degree from Imperial College London, and earned a Ph.D. from University College London, where his dissertation was the sole nominee for the AAAI/ACM SIGAI Outstanding Dissertation Award.
Before joining Peking University in 2022, Yang served as an Assistant Professor at King's College London and was selected for the UK Home Office's Exceptional Talent Scheme; he previously held positions including Principal Researcher at Huawei Research U.K. and Senior Manager at AIG. He has published extensively at top venues including NeurIPS, ICML, ICLR, and in journals such as Nature Machine Intelligence, Artificial Intelligence Journal, and IEEE TPAMI, with work receiving thousands of citations. His contributions have earned awards including the Best Systems Paper Award at CoRL 2020, the Most Visionary Paper Award at AAMAS 2021, the Shining Star Award at WAIC 2022, the ACM SIGAI China Rising Star Award, and the Best Technical Breakthrough Award at Huawei London Research Institute. Yang serves as Area Chair for conferences including ICML, ICLR, NeurIPS, AAAI, IJCAI, AAMAS, and IROS, and as Associate Editor for journals including Scientific Reports, Transactions on Machine Learning Research, and Neural Networks.
Peking University and Fudan researchers use PackingStar RL to set new kissing number lower bounds in dimensions 25-31, revolutionizing high-dimensional sphere packing.
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