Shuxin Lyu

Nihon University

Papers

3

Total Citations

6

H-Index

2

About

Shuxin Lyu is at the forefront of bio-inspired robotics and neuromorphic engineering, bridging the gap between biological neural control and robotic locomotion. His research focuses on understanding how living systems—from human gaits to quadrupedal movement—generate and coordinate motion, then translating those principles into artificial neural networks that can drive robots without conventional microprocessors. In his highly cited 2023 work on spinal cord-like artificial neural networks, Lyu demonstrated that robot movements can be realized through neural network architectures that mimic biological processing, eliminating the need for traditional CPU-software combinations. His 2024 studies further advanced this paradigm by extracting actuator forces and displacements during human walking and running through inverse dynamics simulation, while also analyzing gait efficiency and cost of transport in quadruped robots integrated with neuromorphic circuits. Though early in his career, Lyu’s work has already garnered attention for its novel approach to merging neuroscience with robotics, offering a path toward more natural, energy-efficient, and adaptive robotic systems that operate like their biological counterparts.

Research Focus

Key Achievements

2
H-Index
3
Papers
6
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Extraction of actuator forces and displacements involved in human walking and running and estimation of time-series neural signals by inverse dynamics simulation
2 citations · 2024
📈 Most Prolific Year: 2024 (2 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Nihon University

Top Papers

  1. 1
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  3. 3

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago