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About

Chetan Arora is a leading researcher at the intersection of computer vision, robotics, and assistive technology, whose work is shaping safer, smarter, and more accessible autonomous systems. His most cited paper, “Intelligent Smart Glass for Visually Impaired Using Deep Learning Machine Vision Techniques and Robot Operating System (ROS)” (23 citations), pioneers a wearable system that fuses deep learning with ROS to provide real-time environmental understanding for the blind. Arora’s contributions extend to high-stakes real-time applications: his work on object detection (21 citations) redefines performance metrics beyond mere precision for autonomous driving and industrial robotics, while his “Comprehensive Telerobotic Ultrasound System” (21 citations) directly addressed the COVID-19 pandemic by enabling remote abdominal imaging, reducing infection risk for healthcare workers. Further notable achievements include developing pose estimation for 5-DOF manipulators using on-body markers (7 citations), advancing automated neurosurgical skill evaluation through representation learning (3 citations), and introducing FinderNet (2 citations), a data-augmentation-free loop detection method for LiDAR point clouds that enhances robot navigation robustness. With over 75 total citations and a portfolio spanning assistive wearables, telerobotics, and surgical training, Arora’s research demonstrates a consistent commitment to deploying vision and robotics innovations where they can have immediate, tangible impact on human lives.