Prof. Jinde Cao, Southeast University, China
东南大学首席教授、数学学院院长、理学部主任、江苏国家应用数学（东南大学）中心主任、江苏省网络群体智能重点实验室主任。首届全国创新争先奖获得者，享受国务院政府特殊津贴。先后当选俄罗斯科学院院士、欧洲科学院院士、俄罗斯工程院院士、欧洲科学与艺术院院士、立陶宛科学院院士、非洲科学院院士、巴基斯坦科学院院士、国际系统与控制科学院院士和IEEE Fellow 等。长期从事复杂网络与复杂系统、神经动力学与优化和工程稳定性等研究，先后主持国家重点研发计划项目1项，国家自然科学基金项目9项（含重点项目），教育部博士点基金3项
Title: Network Dynamics and Pinning Control
Abstract: The realm of collective dynamics within complex networks has unveiled fascinating phenomena such as flocking, schooling, and swarming, which arise from the interplay of collections among nodes. Through certain evolutionary mechanisms, local and unordered interactions could lead to global, coordinated behaviors. This fascinating field not only deepens our understanding of natural processes but also holds potential for diverse practical engineering scenarios. In the era of AI 2.0, research areas spanning from the origins of complex networks to multi-agent systems and network collective intelligence remain significant and continue to exhibit their unique charms and functionalities.
In this talk, we will introduce various network dynamics and explore effective control schemes, with a special focus on pinning control. From both theory and application aspects, we will give our research on the following three topics: theory and methods of collective intelligence, intelligent learning, and collaborative control, and efficient collective intelligence-inspired optimization algorithms. Then, we will discuss three basic questions for pinning control: (1) the identification of optimal nodes for control implementation, (2) the design of appropriate pinning control gains, and (3) the optimization of the number of pinned nodes. Lastly, future discussions for networks with different time and space scales, distributed AI technology, and applications will also be elaborated.