Umesh Thillaivasan

Papers

Total Citations

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About

Umesh Thillaivasan is a researcher advancing sustainable waste management and circular economy solutions through intelligent classification systems. His primary research focuses on computer vision and machine learning techniques for sorting waste electrical and electronic equipment (WEEE), a critical challenge in transitioning global supply chains from mined to recycled materials. His most cited work, "RGB-X Classification for Electronics Sorting" (2022), introduces a novel approach that combines standard RGB imaging with additional spectral data to improve the accuracy of disassembling and recovering valuable materials from e-waste streams. This contribution addresses the limitations of conventional shredding and sorting methods, which often fail to efficiently separate complex electronic components. With 5 citations, this paper has already garnered attention from researchers working on sustainable recycling technologies. Thillaivasan’s work is notable for its practical implications: by enhancing material recovery rates, his methods help reduce the carbon footprint of electronics manufacturing and support the development of renewable supply chains. His research sits at the intersection of environmental engineering and artificial intelligence, offering scalable solutions for one of the fastest-growing waste streams globally. For students and researchers interested in applied machine learning for sustainability, Thillaivasan’s work demonstrates how intelligent classification can directly impact real-world recycling challenges.