Yuedong Ku
Papers
4
Total Citations
192
H-Index
4
About
Yuedong Ku is a researcher specializing in robotics, artificial intelligence, and sustainable waste management, with a particular focus on the automated handling of construction and demolition (C&D) waste. His work sits at the intersection of deep learning, computer vision, and robotic systems, addressing one of the most pressing environmental challenges in modern construction: the efficient classification and recycling of demolition materials. Ku's most impactful contribution is his application of deep learning techniques to robotic grasping detection, enabling machines to intelligently identify and sort C&D waste with remarkable precision — a paper that has garnered 90 citations since its 2020 publication. Complementing this, his development of an automatic sorting robot for C&D waste (63 citations) demonstrates his ability to translate algorithmic innovation into practical, deployable systems. His research further extends to optimizing grasping efficiency and combining spatial and spectral features for waste classification, reflecting a comprehensive, multi-faceted approach to the problem. Notably, all four of his most-cited works were published in 2020, signaling a highly productive and focused research period. With nearly 200 combined citations, Ku's contributions are making a meaningful impact on efforts to reduce environmental damage through smarter, AI-driven recycling technologies.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4