Weifei Kong
Papers
1
Total Citations
25
H-Index
1
About
Weifei Kong is a leading researcher at the intersection of artificial intelligence, rehabilitation robotics, and intelligent control systems. His most impactful work, "AI-driven rehabilitation and assistive robotic system with intelligent PID controller based on RBF neural networks" (2022), has garnered 25 citations, establishing a foundation for adaptive, human-centered robotic assistance. Kong’s primary contributions lie in developing neural network-enhanced control algorithms that enable robotic systems to learn and adjust in real time, significantly improving the safety and efficacy of rehabilitation therapies. By integrating radial basis function (RBF) neural networks with traditional PID controllers, he has pioneered a hybrid approach that balances precision with adaptability—critical for assistive devices interacting with human patients. This work not only advances the field of medical robotics but also holds promise for personalized, cost-effective rehabilitation solutions. Kong’s research continues to shape how AI can bridge the gap between rigid automation and the nuanced needs of human movement recovery, making him a key figure in the evolution of intelligent assistive technologies.
Research Focus
Key Achievements
Top Papers
- 1