Li-Ming Chao

About

Li-Ming Chao is a leading researcher in bio-inspired fluid dynamics, focusing on the propulsive mechanisms of aquatic locomotion and their applications to robotic systems. His work centers on understanding how oscillating foils and flexible structures generate thrust, transition from drag to thrust, and interact in complex flow environments. Chao’s major contributions include systematic investigations of nonsinusoidal and asymmetric pitching foils, revealing how chord-wise flexibility and variable pitching rates influence force generation and wake structures—insights critical for designing efficient underwater vehicles. His research on burst-and-coast swimming and side-by-side vortex interactions has advanced knowledge of maneuverability and energy savings in multi-agent systems. With over 185 citations across his top papers, Chao’s impact is evident in studies like his 2018 work on nonsinusoidal foils (44 citations) and his 2021 analysis of asymmetric oscillations (35 citations). Notably, his 2025 paper introduces an interpretable approach using mode decomposition for self-motion estimation in fish-like robots, bridging fluid dynamics and sensing technology. Chao’s work has been published in high-impact journals and is widely referenced by engineers and biologists alike.

Research Focus

Key Achievements

Top Papers

1. 1
   Numerical investigations on the force generation and wake structures of a nonsinusoidal pitching foil

   44 citations · 2018
2. 2
   Drag–thrust transition and wake structures of a pitching foil undergoing asymmetric oscillation

   35 citations · 2021
3. 3
   On the thrust generation and wake structures of two travelling-wavy foils

   19 citations · 2019
4. 4
   Vortex interactions of two burst-and-coast swimmers in a side-by-side arrangement

   16 citations · 2023
5. 5
   On the propulsive performance of a pitching foil with chord-wise flexibility at the high Strouhal number

   16 citations · 2018
6. 6
   Flow map of foil undergoing combined fast and slow pitching

   15 citations · 2021
7. 7
   An interpretable approach to estimate the self-motion in fish-like robots using mode decomposition analysis

   14 citations · 2025
8. 8
   Tailbeat perturbations improve swimming efficiency by reducing the phase lag between body motion and the resulting fluid response

   9 citations · 2024
9. 9
   On the drag–thrust transition of a pitching foil

   9 citations · 2019
10. 10
    On turning maneuverability in self-propelled burst-and-coast swimming

    8 citations · 2024

Key Collaborators

Contact & Links