Daiyao Yi

Papers

Total Citations

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About

Daiyao Yi is a leading researcher in sustainable manufacturing and human-robot collaboration, with a focus on intelligent disassembly systems for remanufacturing. His work addresses the critical challenge of processing end-of-life electronics, where manual disassembly remains slow and inefficient. Yi’s most-cited paper, “Unsupervised Human Activity Recognition Learning for Disassembly Tasks” (2023, 36 citations), pioneers a novel approach to enabling robots to autonomously understand and assist human workers during complex disassembly operations. By developing unsupervised learning methods that recognize worker actions without requiring extensive labeled data, Yi’s research significantly advances the practicality of human-robot collaborative systems in real-world remanufacturing plants. This work has direct implications for improving productivity and reducing waste in the circular economy. Beyond this flagship study, Yi’s broader contributions span sensor-based activity recognition, adaptive control strategies, and ergonomic optimization for human-robot teams. His research has been recognized for its potential to transform labor-intensive recycling industries, earning him invitations to speak at international conferences on sustainable automation. With growing citation impact, Yi is establishing himself as a key voice at the intersection of manufacturing sustainability and intelligent robotics.