Pavlos Mavromatidis
Papers
2
Total Citations
99
H-Index
2
About
Pavlos Mavromatidis is a leading researcher at the intersection of artificial intelligence and sustainable construction, whose work is pioneering the automation of waste management. His primary research areas include deep learning for object detection, construction and demolition waste (CDW) recycling, and the development of intelligent robotic systems for environmental sustainability. Mavromatidis’s most significant contribution is his groundbreaking study on real-time CDW detection, which systematically compares single-stage and two-stage deep learning detectors. This work, which has garnered 95 citations, is central to the development of a successful waste-sorting robot, providing the accurate, fast object detection system essential for automated recycling. By rigorously evaluating state-of-the-art models, he has established a critical benchmark for the field, enabling more efficient and precise separation of materials on construction sites. His research directly addresses the global challenge of construction waste, offering a scalable, AI-driven solution that promises to reduce landfill burden and promote a circular economy. Mavromatidis’s work is not only technically rigorous but also highly applied, bridging the gap between advanced computer vision and practical environmental engineering.
Research Focus
Key Achievements
Top Papers
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