Gangmin Li

The Open University, Gifu University, Xi’an Jiaotong-Liverpool University

Papers

Total Citations

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About

Dr. Gangmin Li’s research spans multi-agent cooperation, discrete-time adaptive control for robotics, and machine learning for social media analytics. His early work introduced a “shifting matrix management” model for multi-agent systems, offering a novel framework for cooperative task allocation, which has garnered 14 citations and laid groundwork for distributed AI coordination. In robotics, Li developed a gain tuning method for discrete-time adaptive control, addressing the critical challenge of sampling-period constraints on gain matrices—a contribution that bridges continuous-time theory with practical digital implementation, earning 6 citations. More recently, he applied machine learning to detect abnormal user behavior in WeChat activities, proposing a two-level stacking model that tackles the “huge and disorder data patterns” of real-world social platforms. This 2019 work, with 4 citations, demonstrates his pivot toward applied data science in high-traffic online environments. Li’s career reflects a trajectory from foundational control theory to contemporary AI-driven social network analysis, showcasing versatility in both theoretical rigor and practical problem-solving. His work remains relevant for researchers in robotics, multi-agent systems, and social media analytics.