Fang-Bao Tian
Papers
3
Total Citations
40
H-Index
3
About
Fang-Bao Tian is a leading researcher in bio-inspired fluid mechanics and computational physics, whose work bridges the gap between biological locomotion and engineered robotic systems. His primary research areas include flapping-wing aerodynamics, fish-like swimming, and fluid–structure interactions, with a strong emphasis on high-fidelity numerical simulations and machine learning integration. Tian’s most-cited paper (2023, 22 citations) reveals how power synchronizations between fluid and structure govern the hovering flight efficiency of passively pitching flapping wings, offering critical insights for micro-aerial vehicle design. His 2022 study (15 citations) pioneered the use of deep reinforcement learning for point-to-point navigation of fish-like swimmers in vortical flows, demonstrating how artificial intelligence can enable autonomous control in complex environments. More recently, Tian has explored the unusual mechanics of tail-first swimming in mosquito larvae (2023), using both numerical and robotic models to uncover the gait kinematics that differentiate this mode from conventional head-first locomotion. His work consistently combines rigorous computational methods with practical engineering applications, making him a key contributor to the development of agile, efficient bio-inspired robots.
Research Focus
Key Achievements
Top Papers
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