Dexin Zhao

National University of Defense Technology

Papers

2

Total Citations

6

H-Index

2

About

Dexin Zhao is a pioneering researcher in bioinspired underwater robotics, with a focus on artificial lateral line (ALL) systems—distributed flow sensor arrays that mimic fish mechanoreception. His work addresses a critical gap: adapting ALL technology for propeller-driven underwater robots, which generate complex wake flows unlike the undulatory motions of robotic fish. In his 2024 study, Zhao demonstrated that propeller wake sensing can reliably estimate lateral motion states, opening new possibilities for maneuvering conventional underwater vehicles without visual or inertial cues. His 2023 paper tackles the optimization challenge of sensor placement using multiresolution dynamic mode decomposition (MrDMD), advancing distributed flow estimation for practical ALL design. Though early in his career, Zhao’s contributions are already cited in the emerging field of bio-inspired sensing, with each of his key papers accumulating 3 citations. His work bridges fundamental fluid dynamics and robotic perception, offering a path toward more autonomous, flow-aware underwater robots. Zhao’s research is essential reading for engineers and scientists interested in sensor placement, flow estimation, and the next generation of underwater vehicle control.

Research Focus

Key Achievements

2
H-Index
2
Papers
6
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Estimating the Lateral Motion States of an Underwater Robot by Propeller Wake Sensing Using an Artificial Lateral Line
3 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: National University of Defense Technology

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago