Papers

2

Total Citations

16

H-Index

2

About

KeWei Song is pioneering the intersection of intelligent manufacturing and biohybrid robotics. His research focuses on adaptive robotic control and the development of insect-computer hybrid systems. In manufacturing, Song introduced a groundbreaking meta-reinforcement learning framework for robotic grinding, enabling autonomous, real-time decision-making for process parameters—a key advancement for precision automation. This work has already garnered 11 citations since its 2025 publication. In biohybrid robotics, Song led the creation of an "insect-computer hybrid robot factory," using vision-guided robotic arms to automatically assemble custom bipolar electrodes onto Madagascar hissing cockroaches. By identifying the pronotum-mesothorax intersegmental membrane as an optimal stimulation site, his team achieved reliable directional and speed control, with the assembly system earning 5 citations. This work represents a major step toward scalable, automated production of cyborg insects for search-and-rescue and environmental monitoring. Song’s dual focus on adaptive manufacturing and biohybrid systems positions him at the forefront of two transformative fields, demonstrating how intelligent robotics can bridge the gap between digital control and biological function.

Research Focus

Key Achievements

2
H-Index
2
Papers
16
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
Adaptive process parameters decision-making in robotic grinding based on meta-reinforcement learning
11 citations · 2025
📈 Most Prolific Year: 2025 (2 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Huazhong University of Science and Technology, Nanyang Technological University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago