Jiyang He
Papers
1
Total Citations
3
H-Index
1
About
Jiyang He is a rising researcher at the intersection of computational fluid dynamics, bio-inspired robotics, and artificial intelligence. His primary research areas include fish schooling hydrodynamics, fluid–structure interaction (FSI), and the application of deep reinforcement learning (DRL) to complex biological locomotion. He is best known for his pioneering 2025 study on modal switching and energy efficiency mechanisms in fish schooling under low hydrodynamic pressure environments. By integrating DRL algorithms with an immersed boundary-based FSI numerical simulation framework, He’s work provides the first comprehensive computational model demonstrating how schooling fish autonomously adapt their formation and swimming modes to minimize energy expenditure. This contribution bridges a critical gap between biological observation and engineering application, offering foundational insights for designing more efficient autonomous underwater vehicles and robotic swarms. Although early in his career—with his most-cited paper currently accumulating 3 citations—the novelty and interdisciplinary rigor of his approach signal a promising trajectory. He’s research stands out for its innovative fusion of machine learning with classical biomechanics, positioning him as an emerging voice in the study of adaptive locomotion in dynamic fluid environments.
Research Focus
Key Achievements
Top Papers
- 1