Associate Professor, Hunan Institute of Science and Technology, China
Dr. Jianhui Wu is an accomplished Associate Professor at the Hunan Institute of Science and Technology, China. With a strong background in system control, optimization, and visual navigation, he has made significant contributions to the field of autonomous systems. His research focuses on advanced control technologies, particularly in multi-agent systems and obstacle avoidance. As an IEEE member, Dr. Wu actively collaborates with the scientific community, publishing impactful studies in high-ranking journals. His work is widely cited, showcasing his influence in the academic and industrial sectors.
Publication Profile
🎓 Education
Dr. Wu earned his Ph.D. from Changsha University of Science and Technology, China, in 2019. His doctoral research laid the foundation for his expertise in system control, signal processing, and visual navigation. His academic journey has been marked by a deep commitment to solving complex problems in autonomous systems and optimization.
💼 Experience
Currently serving as an Associate Professor, Dr. Wu is affiliated with the School of Information and Communication at Guilin University of Electronic Technology. Over the years, he has led several research projects funded by the Zhuang Autonomous Region, working on cutting-edge control mechanisms for autonomous multi-agent systems. His contributions span both theoretical advancements and practical applications in the fields of artificial intelligence, automation, and transportation optimization.
🏆 Awards and Honors
Dr. Wu’s work has been widely recognized, with multiple grants supporting his research in intelligent systems and control optimization. His research output has earned high citations in SCI-indexed journals, further cementing his reputation as a leading researcher in his domain.
🔬 Research Focus
Dr. Wu’s research primarily revolves around system control and optimization, visual navigation, and signal processing. His groundbreaking studies on multi-agent autonomous systems explore innovative flocking control mechanisms that enhance obstacle avoidance, navigation, and collaborative behaviors. His research has contributed to designing efficient, self-organizing, and adaptive autonomous systems, essential for advancements in robotics and artificial intelligence.
📌 Conclusion
Dr. Jianhui Wu is a dedicated researcher whose contributions to system control and multi-agent coordination continue to shape the future of automation and intelligent transportation. With numerous publications in top-tier journals and significant industry collaborations, his work is paving the way for smarter, more autonomous systems.
📚 Publications
Fuzzy Flocking Control for Multi-Agents Trapped in Dynamic Equilibrium Under Multiple Obstacles – International Journal of Control, Automation and Systems, 2024 (DOI: 10.1007/s12555-022-0950-6)
Virtual-Leader Split/Rejoin-Based Flocking Control With Obstacle Avoidance for Multi-Agents – International Journal of Control, Automation and Systems, 2024 (DOI: 10.1007/s12555-022-0950-6)
Anonymous Flocking With Obstacle Avoidance via the Position of Obstacle Boundary Point – IEEE Internet of Things Journal, 2024 (DOI: 10.1109/jiot.2024.3465881)
Obstacle Boundary Point and Expected Velocity-Based Flocking of Multiagents with Obstacle Avoidance – International Journal of Intelligent Systems, 2023 (DOI: 10.1155/2023/1493299)
Optimization Scheme of Fine Toll and Bus Departure Quantity for Bottleneck Congestion Management – Complexity, 2021 (DOI: 10.1155/2021/5518502)
Optimization Scheme of Tradable Credits and Bus Departure Quantity for Travelers’ Travel Mode Choice Guidance – Journal of Advanced Transportation, 2020 (DOI: 10.1155/2020/6665161)
Price Regulation Mechanism of Travelers’ Travel Mode Choice in the Driverless Transportation Network – Journal of Advanced Transportation, 2020 (DOI: 10.1155/2020/9191834)
Guidance Optimization of Travelers’ Travel Mode Choice Based on Fuel Tax Rate and Bus Departure Quantity in Two-Mode Transportation System – Journal of Advanced Transportation, 2020 (DOI: 10.1155/2020/4190632)
A Day-to-Day Stochastic Traffic Flow Assignment Model Based on Mixed Regulation – IEEE Access, 2020 (DOI: 10.1109/access.2019.2962864)
Robust Optimization of Sequence Decision in Urban Road Construction – Computer Science, 2018