Papers
1
Total Citations
2
H-Index
1
About
Yajun Li is an emerging researcher at the intersection of human-centered design, affective computing, and industrial robotics, with a focus on bridging the gap between user experience and intelligent machine aesthetics. Li's most notable work introduces a Kansei-oriented morphological design methodology for industrial cleaning robots, a pioneering contribution that integrates Extenics-based semantic quantification with eye-tracking analysis to systematically translate users' emotional and sensory preferences into robot form design. This research addresses a critical challenge in the Industry 4.0 landscape, where user demands have shifted beyond functionality toward richer, experience-driven interactions with industrial systems. By combining psychological measurement frameworks with biometric data capture, Li's approach moves the field beyond subjective designer intuition toward empirically grounded, user-validated design processes. Though early in citation accumulation with 2 citations to date, this 2025 publication signals a timely and relevant research agenda as human-robot interaction becomes increasingly central to modern manufacturing environments. Li's work holds particular promise for students and practitioners seeking rigorous, data-driven methods for emotionally intelligent product and robot design in next-generation industrial settings.
Research Focus
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Top Papers
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