Papers
6
Total Citations
122
H-Index
4
About
Zhiwen Deng is a dynamic researcher at the intersection of human-robot interaction, computer vision, and gesture-based communication systems. His work spans two complementary frontiers: robotic teleoperation and skeleton-based recognition of human motion, making him a notable contributor to the growing field of intelligent human-machine systems. Deng's most celebrated contribution, "Dual-Hand Motion Capture by Using Biological Inspiration for Bionic Bimanual Robot Teleoperation" (2023, 56 citations), demonstrates his innovative approach to transferring natural human dexterity to robotic systems — a critical challenge in modern robotics. Alongside this, his development of multi-feature, multi-stream neural network architectures for real-time action recognition has earned significant scholarly attention, with his skeleton-based action recognition framework accumulating 31 citations in its debut year. Particularly notable is Deng's sustained focus on sign language recognition, where he has proposed multiple advanced learning frameworks — including TMS-Net and SML — designed to improve accessibility and communication technology for hearing-impaired communities. Collectively amassing over 120 citations, his body of work reflects both technical rigor and meaningful societal impact, positioning him as an emerging authority in embodied AI and assistive human-computer interaction research.
Research Focus
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Top Papers
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