Papers
2
Total Citations
6
H-Index
2
About
Zaiming Geng is a pioneering researcher at the intersection of soft robotics and computer vision, whose work addresses critical challenges in human-machine interaction and environmental perception. His primary research areas include soft pneumatic actuators for rehabilitation robotics and deep learning-based image enhancement for degraded visual environments. Geng’s most impactful contribution is the design and experimental validation of a nested pneumatic soft actuator for hand exoskeletons, a breakthrough that overcomes the weight and safety limitations of traditional rigid exoskeletons. This work, already garnering 4 citations since its 2025 publication, demonstrates how biomimetic soft structures can restore hand motor function for workers suffering from repetitive strain injuries. In parallel, Geng has advanced underwater computer vision through a hybrid U-Net-Transformer architecture with recurrent multi-scale modulation, achieving state-of-the-art enhancement of severely degraded underwater imagery. This dual expertise—bridging physical hardware design with algorithmic perception—positions Geng as a uniquely versatile innovator. His work on the soft hand exoskeleton, in particular, represents a paradigm shift in assistive technology, offering a lightweight, compliant alternative that minimizes secondary injury risks while maximizing functional support. With both papers published in 2025, Geng is rapidly establishing himself as a rising force in rehabilitation robotics and computational imaging.
Research Focus
Key Achievements
Top Papers
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