Academic Report of School of Mathematical Sciences [2026] No. 071

(Series Report for High-Level University Construction No. 1330)

Title：Intelligence Science: The Severe Challenges at the Frontiers of Contemporary Mathematics and How to Address Them

Speaker：Dr. Jiaosu Wu (Chinese Academy of Sciences)

Time：16:30-17:30, June 28, 2026

Location：Conference Room 304, Alumni Plaza, Yuehai Campus, Shenzhen University

Abstract:According to John von Neumann, the founder of Intelligence Science, the field encompasses both natural intelligence and artificial intelligence, and its fundamental purpose is to safeguard human dignity and security. This requires correcting the mistake—both internationally and domestically—of focusing solely on artificial intelligence while neglecting human intelligence, thereby thoroughly overcoming the current limitation of prioritizing large models alone.

Intelligence Science comprises three major principles: the Strategic Correlativity Principle, the Strategy Causality Law, and the Fundamental Theorem of Strategic Causal Learning. Mathematically, Intelligence Science poses significant challenges to the frontiers of contemporary mathematics; for example, within the Strategic Correlativity Principle, strategy-dependent stochastic variables present challenges to strategy-independent stochastic variables, among other issues. From the perspectives of the history of mathematics and the history of science, Intelligence Science is an emerging foundational science with a promising future. We warmly invite talented young mathematicians to join the ranks of mathematical research in Intelligent Science.

Speaker Profile：Ph.D. from the Institute of Science and Technology Strategy and Consulting, Chinese Academy of Sciences; member of the Standards Group of the Chinese Academy of Sciences Artificial Intelligence Alliance; adjunct researcher at the Institute of Intelligent Law, East China University of Political Science and Law; advisor to the Center for the Rule of Law and Social Governance at the Zhejiang Tsinghua Yangtze River Delta Research Institute; and researcher at the Smale Institute for Mathematics and Computation. He previously served as director of the project office for “Game Theory-Based Decision-Making under Incomplete Information,” a major project on next-generation artificial intelligence under the Ministry of Science and Technology, and as an advisor to the Baidu Public Policy Institute (Legal Research Center).

Guided by the ideas of mathematicians John von Neumann, Chi-Siang Chen, and Robert Aumann, and based on the game-theoretic Helmholtz-Hodge orthogonal decomposition theorem, Dr. Wu spent 22 years developing the Strategy Correlation Principle (SCP), the Strategy Causality Law (SCL), the Fundamental Theorem of Strategy Causal Learning (FTSCL), and the Graceful AI theory. Dr. Wu’s research focuses on spatiotemporal game dynamics, axiomatic game theory, axiomatic learning theory, and nuclear methods, as well as their applications in mechanism design, information design, action design, robust neural network design, controllable multimodal pre-trained large models (LLM/AIGC, VLA/AIGA), causal inference, and multi-robot dynamics. Dr. Wu’s recent research projects include the Ministry of Science and Technology’s New Generation Artificial Intelligence Major Project on “Game-Theoretic Decision-Making under Incomplete Information,” the Chinese Academy of Sciences’ Advisory Review Project on “Artificial Intelligence Ethics,” the Cyberspace Administration of China’s Research Project on “Artificial Intelligence Ethical Guidelines,” the Ministry of Industry and Information Technology’s Electronic Science and Technology Committee’s “Research on the Technical Essence and Core Industries of Artificial Intelligence,” and the Shanghai “Science and Technology Innovation Action Plan” AI Technology Support Special Project titled “Theory and Algorithms for Large-Scale Distributed Artificial Intelligence Based on Stochastic Game Dynamics.” Dr. Wu’s papers have been cited by scientists at world-renowned research institutions and universities, including Google, Stanford University, Cornell University, and Stockholm University; he has co-authored four books and is preparing to publish a monograph titled Mathematical Principles of Intelligent Science.

Dr. Wu has served as an invited or keynote speaker, program committee member, organizer, or co-organizer for numerous top-tier academic conferences, including the World Robot Conference, the China Computer Conference, the satellite conference of the 8th International Congress on Industrial and Applied Mathematics, the 36th Xiangshan Science Conference, the 2019 AI Science Frontiers Conference, and the Causal Inference Forum at the 2024 World Artificial Intelligence Conference. He is a Senior Member of the Chinese Computer Society (CCF) and a member of its Artificial Intelligence and Pattern Recognition Technical Committee; a member of the Machine Games Technical Committee of the Chinese Association for Artificial Intelligence (CAAI); and a council member of the Game Theory Technical Committee of the Chinese Operations Research Society.

Faculty and students are welcome to attend!

Invited by: Jian Lu

School of Mathematical Sciences

June 27, 2026