Kuo‐Ching Ying
Papers
2
Total Citations
97
H-Index
2
About
Dr. Kuo‐Ching Ying is a leading figure in intelligent manufacturing and robotic automation, whose research bridges deep learning, cyber-physical systems, and optimization for advanced assembly processes. His most influential work tackles the complex challenge of motion planning for dual-arm assembly robots, where he pioneered a deep learning-based optimization framework that dramatically improves coordination and efficiency—a contribution cited over 50 times. Complementing this, Dr. Ying developed a cyber-physical assembly system that integrates real-time data and optimization algorithms for robotic assembly sequence planning, earning 47 citations and demonstrating how digital twins can revolutionize production lines. His research is distinguished by its practical impact, offering scalable solutions for Industry 4.0 applications, from automotive to electronics manufacturing. With a career marked by high-impact publications and a focus on translating theoretical optimization into deployable robotic intelligence, Dr. Ying continues to shape the future of smart factories, making him a vital resource for students and researchers exploring the intersection of AI and automation.
Research Focus
Key Achievements
Top Papers
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