About

Hai-Tao Zhang is a leading researcher in cyber-physical systems, multi-agent flocking, and human-robot collaboration, whose work bridges theoretical modeling and real-world engineering applications. His most influential contribution is the data-driven discovery of cyber-physical systems (2019, 168 citations), which addresses the challenge of modeling complex systems like smart grids and intelligent manufacturing by integrating software with physical processes. Zhang has also made significant strides in understanding collective behavior, notably through his studies on flocking in bounded spaces (2013, 41 citations) and the hierarchical leadership dynamics in pigeon flocks (2016, 34 citations), which reveal how slight changes in attractive/repulsive functions can trigger dramatic aggregation pattern transitions (2011, 20 citations). His recent work extends to practical robotics, including sectorial coverage control in non-convex environments (2023, 17 citations) and human multi-robot cooperative manipulation (2023, 4 citations), demonstrating a commitment to advancing autonomous systems. With over 300 total citations across his publications, Zhang’s research has profound implications for robotics, swarm intelligence, and industrial automation, making him a pivotal figure in the evolution of intelligent, collaborative machines.

Research Focus

Key Achievements

5
H-Index
12
Papers
301
Total Citations
25
Avg Citations/Paper
🏆 Most Cited Paper
Data driven discovery of cyber physical systems
168 citations · 2019
📈 Most Prolific Year: 2019 (3 Papers)
🤝 Key Collaborators: 34
🏛 Institutions: Huazhong University of Science and Technology, ITRI International, Bridge University, Huazhong University of Science and Technology Hospital

Top Papers

  1. 1
    Data driven discovery of cyber physical systems
    168 citations · 2019
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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago