Zhiqiang Fang

South China University of Technology, Shanghai Ocean University

Papers

Total Citations

H-Index

About

Zhiqiang Fang is a rising researcher at the intersection of advanced materials and intelligent systems, whose work bridges soft robotics, flexible electronics, and computer vision. His most cited study (56 citations) introduces an anisotropic, muscle-like conductive composite hydrogel reinforced by lignin and cellulose nanofibrils—a breakthrough that mimics natural muscle structure to achieve both high mechanical strength and superior conductivity. This innovation directly addresses a critical bottleneck in developing durable flexible electronic devices and smart soft robots. In parallel, Fang’s YOLOv6-ESG lightweight seafood detection method (19 citations) demonstrates his versatility, tackling the challenge of automated underwater object detection in complex, low-visibility environments. By optimizing convolutional neural networks for underwater robots, this work has significant implications for sustainable aquaculture and marine resource management. Fang’s ability to move seamlessly from biomimetic material design to practical AI-driven applications marks him as a multidisciplinary talent. His contributions not only advance fundamental science but also offer tangible solutions for next-generation robotics and environmental monitoring, making his research highly relevant for students and engineers working at the nexus of materials science and artificial intelligence.