Papers
5
Total Citations
61
H-Index
4
About
Mu-Yen Chen is a pioneering researcher at the intersection of cognitive computing, robotics, and intelligent systems, with a focus on human–machine interaction and healthcare applications. His work spans three key areas: cognitive computing for service industries, emotion recognition using IoT and thermal imaging, and robotic musicianship enhanced by generative adversarial networks. Chen’s major contributions include developing a hybrid cognitive computing model for food services (22 citations), which optimizes decision-making in dynamic environments, and a data fusion framework for ADHD emotion recognition (18 citations) that integrates thermal image and IoT data to improve behavioral diagnosis. He has also advanced robotic creativity through least squares and sequence GANs (12 citations), enabling autonomous music generation. Notably, Chen’s recent work on consumer electronics robotics (2025) leverages large language models within a trustworthy AI framework, addressing labor shortages in elderly care. His editorial on neural network-based robot trajectory learning further underscores his leadership in fast, adaptive robotics. With over 60 citations across his top papers, Chen’s research is driving practical, ethical AI solutions for real-world challenges.
Research Focus
Key Achievements
Top Papers
- 1Hybridization of cognitive computing for food services22 citations · 2020
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