Ying Liang

Papers

Total Citations

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About

Ying Liang is a leading researcher in human-robot collaboration, with a focus on democratizing robot programming for non-expert users. Their work addresses a critical barrier to cobot adoption in industry: the shortage of skilled programmers. Liang’s most cited paper, "Evaluation of a robot programming framework for non-experts using symbolic planning representations" (2017, 8 citations), pioneers a framework that enables workers without technical backgrounds to program collaborative robots through intuitive symbolic planning. This contribution has been instrumental in lowering the entry threshold for companies seeking to integrate cobots into manufacturing and service settings. By bridging the gap between complex robotics and practical usability, Liang’s research directly impacts workforce training and industrial automation efficiency. Their work is recognized for its applied significance, offering a scalable solution to the programming bottleneck that hinders widespread cobot deployment. Liang’s achievements underscore a commitment to making advanced robotics accessible, fostering safer and more productive human-robot workplaces.