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About

Hemanth Mohan is an emerging researcher at the intersection of computer vision, embedded systems, and sustainable technology. His work primarily focuses on applying deep learning and IoT for real-world environmental and agricultural challenges. Mohan’s most cited paper, “Waste Detection and Classification Using Yolo Algorithm and Sensors” (2023, 6 citations), addresses India’s critical solid waste crisis by designing an automated system to identify and sort garbage, aiming to improve collection efficiency in densely polluted metro cities. He further extends this vision to precision agriculture with “Autonomous IoT-Integrated Tomato Plant Disease Detection: Harnessing YOLOv8 Algorithm and Micro-Navigation for Precision Agriculture” (2024, 1 citation), where he combines advanced object detection with micro-navigation to protect vital crops like tomatoes from disease. Demonstrating a unique breadth, Mohan also explores neuromorphic engineering in “Design of a bio-inspired CMOS circuit realizing features of binocular rivalry between left and right eye” (2013, 2 citations), mimicking a complex visual brain phenomenon on silicon. Though early in his career, Mohan’s work showcases a compelling drive to translate cutting-edge AI and circuit design into tangible solutions for pressing societal problems, from waste management to food security.