Papers

7

Total Citations

92

H-Index

4

About

Jialei Song is a leading researcher in the field of biomimetic robotics and bio-inspired hydrodynamics, with a focus on translating the complex locomotion of aquatic organisms into efficient engineered systems. Her work bridges the gap between biological principles and robotic implementation, particularly through her foundational contributions to the Lighthill fish swimming model. In her highly cited 2018 paper (40 citations), Song introduced a transformative method for building biomimetic robot fish that overcomes traditional challenges of structural complexity and propulsive inefficiency. She has further advanced the field by studying the kinematic patterns of fish undulatory locomotion (26 citations), revealing why robotic systems must follow biological formulas. Her research extends to the roles of median fins in carangiform swimming, the effects of caudal fin bending kinematics on performance, and the unique locomotion strategies of midge larvae at intermediate Reynolds numbers. With over 90 total citations, Song’s work has significantly impacted the design of more efficient, agile underwater robots. Her notable achievements include developing an active-and-compliant propulsion mechanism for untethered robot fish capable of three-dimensional locomotion and depth control, as well as modeling the hydrodynamics and musculature actuation during fish fast-start maneuvers—critical insights for predator-prey dynamics in robotics.

Research Focus

Key Achievements

4
H-Index
7
Papers
92
Total Citations
13
Avg Citations/Paper
🏆 Most Cited Paper
Toward a Transform Method From Lighthill Fish Swimming Model to Biomimetic Robot Fish
40 citations · 2018
📈 Most Prolific Year: 2023 (3 Papers)
🤝 Key Collaborators: 17
🏛 Institutions: Chinese University of Hong Kong, Dongguan University of Technology

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago