Mengjun Fang

Papers

Total Citations

H-Index

About

Mengjun Fang is a robotics researcher whose work bridges mechanical design, automation, and intelligent control. His primary research areas include in-pipe robotics, autonomous manufacturing systems, and surgical robotics, with a growing focus on deep-learning-driven manipulation. Fang’s most cited work, “Design and analysis of a novel active screw-drive pipe robot” (2018, 29 citations), introduces an innovative in-pipe robot capable of navigating both circular and square pipe structures using a unique wall-pressing suspension mechanism—a significant contribution to confined-space inspection and maintenance. He also developed an autonomous soldering robot for USB wires (2020, 7 citations), addressing critical manual pre-processing bottlenecks in consumer electronics manufacturing. In the medical domain, Fang explored voice-controlled robotic arms for hysterectomy (2019, 3 citations), integrating MFCC feature extraction with convolutional neural networks for intuitive surgical assistance. His recent work on deep-learning-based robotic manipulation of flexible PCBs (2020, 3 citations) tackles the deformation challenges inherent in handling small, flexible circuit boards. With a total of 42 citations across his key publications, Fang’s contributions demonstrate a clear trajectory from mechanical innovation toward intelligent, adaptive automation—making his research relevant to students and engineers interested in practical, industry-driven robotics solutions.