Eujin Pei
Papers
1
Total Citations
42
H-Index
1
About
Eujin Pei is a leading researcher at the intersection of artificial intelligence, robotics, and sustainable manufacturing, with a primary focus on human-robot collaboration and circular economy systems. His most cited work, "Partially observable deep reinforcement learning for multi-agent strategy optimization of human-robot collaborative disassembly: A case of retired electric vehicle battery" (2024, 42 citations), exemplifies his pioneering contributions to intelligent automation for end-of-life product processing. Pei’s research addresses critical challenges in remanufacturing by developing advanced reinforcement learning frameworks that enable robots to operate effectively under partial observability, coordinating complex disassembly tasks with human workers. This work is particularly impactful for the recycling of retired electric vehicle batteries, a pressing environmental and industrial problem. By integrating multi-agent strategy optimization, Pei has advanced the practical deployment of adaptive, safe, and efficient human-robot teams in manufacturing environments. His contributions are vital for achieving sustainable production goals, and his research continues to shape the future of smart, green manufacturing systems.
Research Focus
Key Achievements
Top Papers
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