Papers
7
Total Citations
526
H-Index
7
About
Qiyue Wang is a pioneering researcher at the intersection of advanced manufacturing, human-robot interaction, and intelligent automation, with a particular focus on revolutionizing welding technology through cutting-edge digital tools. His work has garnered substantial recognition in the field, accumulating over 520 citations across his most influential publications. Wang's most celebrated contribution, "Digital Twin for Human-Robot Interactive Welding and Welder Behavior Analysis" (2020, 163 citations), established him as a leading voice in applying digital twin technology to manufacturing environments, creating immersive platforms where human expertise and robotic precision converge. Building on this foundation, his trilogy of virtual reality-based welding studies (2019) collectively amassed over 200 citations, demonstrating how VR interfaces and human intention recognition can make robotic welding systems more intuitive and accessible to skilled workers. His research extends into adaptive and intelligent manufacturing systems, exploring how machine learning and deep learning can autonomously detect weld quality indicators like joint penetration — capabilities that replicate the nuanced judgment of experienced welders. Wang's body of work represents a compelling vision for the future of smart manufacturing: one where human skill is amplified rather than replaced, bridging cyber-physical systems with real-world industrial demands.
Research Focus
Key Achievements
Top Papers
- 1Digital Twin for Human-Robot Interactive Welding and Welder Behavior Analysis163 citations · 2020
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- 3Adaptive Intelligent Welding Manufacturing75 citations · 2021
- 4Virtual Reality Robot-Assisted Welding Based on Human Intention Recognition67 citations · 2019
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