Jian Fei
Papers
6
Total Citations
74
H-Index
5
About
Jian Fei is a pioneering researcher in robotics and medical image processing, whose work bridges mechanical design, intelligent control, and healthcare diagnostics. His primary research areas include fault diagnosis for industrial robots, hybrid robot kinematics and dynamics, continuum robot control, and lung nodule detection in CT imaging. Fei’s major contributions include developing a novel fault diagnosis method combining manifold learning, Treelet Transform, and Naive Bayes, achieving 27 citations for its practical application in industrial settings. He also designed a five-degrees-of-freedom hybrid robot (16 citations) integrating a Delta robot with a serial mechanism, advancing precision in automation. In healthcare, Fei’s work on lung nodule pre-diagnosis and insertion path planning (11 citations) leverages deep learning to improve early cancer screening. His research on reinforcement learning for continuum robots (8 citations) addresses data inefficiency, while his unit-compressible modular robotic system (9 citations) enables self-configuration for adaptive tasks. Fei’s bionic snake-mouth end-effector (3 citations) showcases his creativity in bio-inspired design. With over 74 citations across his top papers, Fei’s interdisciplinary approach—combining robotics, AI, and medical imaging—positions him as a key innovator in intelligent systems and healthcare technology.
Research Focus
Key Achievements
Top Papers
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- 3Lung nodule pre-diagnosis and insertion path planning for chest CT images11 citations · 2023
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