Papers
4
Total Citations
68
H-Index
4
About
Chenglin Yu is a researcher whose work bridges artificial intelligence, robotics, and sustainable construction. His primary research areas include machine vision for social robots, digital twin technology, and waste management optimization. Yu’s most notable contribution is his pioneering application of digital twins to building demolition waste trading, a field where he has developed frameworks to increase recycling rates and reduce environmental impact. His 2023 paper, "Trading building demolition waste via digital twins," has garnered 22 citations, while a 2025 demonstrative case study extends this work with 8 citations. Earlier, Yu explored face recognition frameworks integrating adversarial neural networks for social robots, a paper that, despite being retracted, received 33 citations. He has also contributed to robotics logistics with an efficient storage strategy for robotic warehouses (5 citations). Yu’s work is particularly impactful for its practical focus on solving real-world environmental challenges through computational methods. His digital twin research directly addresses the low recycling rates in construction waste management, offering a scalable solution that combines IoT, simulation, and market mechanisms. For students and researchers, Yu exemplifies how interdisciplinary approaches—merging AI, robotics, and sustainability—can drive meaningful innovation.
Research Focus
Key Achievements
Top Papers
- 1
- 2Trading building demolition waste via digital twins22 citations · 2023
- 3
- 4An efficient storage strategy for robotic warehouse5 citations · 2025