Jingyi Bai
Papers
2
Total Citations
9
H-Index
2
About
Jingyi Bai is a pioneering researcher in biomimetic underwater robotics, with a primary focus on manta ray-inspired robotic systems. Her work bridges the gap between biological propulsion mechanisms and practical engineering applications, particularly in developing energy-efficient swimming robots. Bai's major contributions include the application of deep learning methods to predict hydrodynamic parameters for manta ray robots, significantly reducing the need for extensive underwater experiments—a breakthrough detailed in her 2022 paper, which has garnered 6 citations. More recently, her 2025 study on one-degree-of-freedom intermittent propulsion systems has advanced the understanding of how manta-like robots can mimic the flapping-and-gliding techniques of real mantas to minimize energy consumption. This work, with 3 citations, demonstrates her ability to translate complex biological kinematics into simplified, implementable robotic designs. Bai's research is notable for its practical impact on improving swimming and turning speeds in autonomous underwater vehicles, offering a data-driven pathway to more efficient robotic locomotion. Her innovative approach positions her as a key contributor to the future of soft robotics and bio-inspired engineering.
Research Focus
Key Achievements
Top Papers
- 1
- 2