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About

Jianhong Yang is a robotics and computer vision researcher whose work has made significant strides in automating the sorting and management of construction and demolition (C&D) waste — a growing environmental challenge worldwide. Yang's research sits at the intersection of deep learning, robotic systems, and sustainable waste management, addressing the urgent need for intelligent recycling solutions. Yang's most impactful contribution applies deep learning to robotic grasping detection for C&D waste sorting, garnering 90 citations since its 2020 publication. Complementing this, Yang led the development of a fully automatic sorting robot for C&D waste (63 citations) and advanced RGB-D sensor fusion models to improve waste detection accuracy (54 citations). Together, these works form a cohesive and influential body of research that has helped define the emerging field of AI-driven waste robotics. Yang further refined these systems by optimizing grasping efficiency and explored combining spatial and spectral features for waste classification, demonstrating a methodical, systems-level approach to the problem. Earlier work on robotic inspection systems for small pipelines signals a longstanding interest in applied robotics across challenging environments. With over 240 cumulative citations, Yang's research has become a key reference point for engineers and scientists working to build smarter, more sustainable waste management technologies.