Zhongwei Tan
Papers
3
Total Citations
105
H-Index
3
About
Zhongwei Tan is a leading researcher in the field of optical fiber sensing, with a focus on integrating deep learning with fiber specklegram analysis for advanced tactile and bending measurements. His pioneering work centers on using multimode fiber (MMF) speckle patterns—captured by CCDs—to detect and classify mechanical deformations with high precision. Tan’s major contributions include developing a deep learning-based method for bending recognition (2020, 63 citations), which decodes mode interference changes caused by curvature, and a sensitized plastic fiber sensor for multi-point bending measurement (2021, 31 citations), overcoming challenges in distinguishing closely spaced bending points. He also introduced a reflective optical tactile sensor (2022, 11 citations) that uses a 3D-printed elastic probe with embedded single-mode and multimode fibers to identify contact positions. These innovations have significant implications for robotics, structural health monitoring, and human-machine interfaces. With over 100 combined citations, Tan’s work demonstrates how machine learning can transform traditional fiber optics into intelligent, high-resolution sensing systems, making him a notable figure in smart sensor technology.
Research Focus
Key Achievements
Top Papers
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