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About

Dongxu Ma is a rising researcher at the forefront of human-robot collaboration for next-generation manufacturing, with a focus on Industry 5.0 paradigms. His work centers on developing intelligent, proactive systems that enable seamless cooperation between humans and robots in assembly tasks. Ma’s key contributions include pioneering deep learning-enabled human-cyber-physical fusion methods that allow robots to anticipate and respond to human actions in real time, significantly enhancing both efficiency and ergonomics. His most cited paper, "A deep learning-enabled human-cyber-physical fusion method towards human-robot collaborative assembly" (2023), has already garnered 48 citations, reflecting its impact on the field. He has also advanced proactive robotic manipulation control through large and small-scale model fusion, and conducted a systematic review on vision-based human assembly intention recognition, establishing a foundational framework for human-centric smart manufacturing. Ma’s work is notable for bridging theoretical AI models with practical industrial applications, positioning him as a key contributor to the evolution of adaptive, collaborative manufacturing systems that prioritize worker well-being alongside productivity.