Papers
5
Total Citations
81
H-Index
4
About
Guojun Mao is a versatile researcher whose work spans smart materials, biomedical engineering, computer vision, and human-machine interaction. His research interests reflect a rare interdisciplinary breadth, bridging materials science with intelligent sensing and deep learning-based recognition systems. Among his most notable contributions is his pioneering work on self-assembly polysaccharide network hydrogel sensors, which demonstrates impressive properties including toughness, anti-freezing capability, and electrical conductivity across wide working conditions — a significant advancement for wearable and flexible electronics that has already attracted over 30 citations since its 2024 publication. In the realm of deep learning, Mao developed the Multibranch Attention (M3Att) mechanism, a lightweight yet powerful module for improving object detection networks, earning 22 citations for its practical impact on computer vision architectures. His 2020 work on predicting human joint moments using neural networks informed by the Hill Muscle Model has gathered 18 citations, underscoring its relevance to rehabilitation engineering and human-robot interaction. Additional contributions to marine organism detection further illustrate his commitment to applying intelligent algorithms to real-world challenges. Collectively, Mao's work represents a compelling fusion of materials innovation and artificial intelligence methodology.
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