Haiteng Wu
Papers
3
Total Citations
90
H-Index
3
About
Haiteng Wu is an emerging researcher at the forefront of human-robot interaction, motion sensing, and digital twin technologies. His work centers on developing intelligent systems that bridge the physical and digital worlds to enhance collaboration between humans and robots. Wu's most influential contribution, an attention-based deep learning framework for inertial motion recognition and estimation in human-robot collaboration, has garnered 53 citations since 2023, demonstrating the field's rapid uptake of his methodologies. Building on this foundation, his pioneering work on Human Motion Digital Twin (HMDT) — which has already accumulated 27 citations in just one year — advances a human-centric paradigm for capturing and applying motion data to support human well-being and safety in collaborative environments. Wu has also pushed the boundaries of remote interaction through his development of a Phygital Twin-driven robot avatar enabling China–Sweden teleoperation, reflecting both the international scope and practical ambition of his research agenda. Collectively, his contributions signal a distinctive research vision: leveraging deep learning and digital twin architectures to make human-robot systems more intuitive, responsive, and ultimately more human. Wu represents a promising voice in the next generation of human-centric robotics research.
Research Focus
Key Achievements
Top Papers
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