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About

Jianxun Wang is a robotics researcher whose work centers on bio-inspired underwater robotics, dynamic modeling, and autonomous control systems. He is best known for his pioneering contributions to the dynamic modeling of carangiform robotic fish, where he developed a novel framework merging rigid-body dynamics with Lighthill's large-amplitude elongated-body theory — work that has garnered 36 citations and established a foundational reference in the field. His research extends beyond modeling into practical applications, including the development of SOAR, a smartphone-integrated robotic fish system designed for vision-based aquatic debris monitoring, demonstrating his commitment to environmentally relevant robotics solutions. Wang has also advanced control methodology for underwater robots, applying backstepping techniques to develop hybrid target-tracking controllers, and employed evolutionary multiobjective optimization — specifically the NSGA-II algorithm — to balance swimming performance and energy efficiency in flexible-fin robotic fish designs. Collectively, his body of work bridges theoretical biomechanics with real-world engineering implementation, making meaningful contributions to aquatic robotics, autonomous surveillance systems, and bio-inspired design optimization. His research provides valuable tools and frameworks for students and engineers working at the intersection of robotics, fluid dynamics, and environmental monitoring.