Adarsh Ghimire

Khalifa University of Science and Technology

Papers

Total Citations

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About

Adarsh Ghimire is an emerging researcher specializing in computer vision, robotics, and intelligent recognition systems. His work addresses practical challenges at the intersection of automated tracking and real-time human detection, with a focus on making sophisticated algorithms viable for deployment in resource-constrained environments. Ghimire's most notable contribution is his 2023 dataset and benchmark study on robot-person tracking in uniform appearance scenarios, which garnered 9 citations and fills a critical gap in the field. Recognizing that existing datasets failed to capture the complexities of tracking individuals wearing similar clothing — a common challenge in security, surveillance, and autonomous driving applications — he introduced a dedicated resource to help researchers rigorously evaluate tracking algorithms under these demanding conditions. Complementing this work, his 2022 study on real-time face recognition systems, which earned 8 citations, tackled the persistent computational bottleneck preventing high-accuracy recognition models from being practically deployed. By addressing the trade-off between performance and efficiency, Ghimire contributed meaningful progress toward accessible, real-world AI applications. Though early in his career, Ghimire's research demonstrates a consistent focus on bridging the gap between theoretical computer vision advances and their practical, real-world implementation in autonomous and security-oriented systems.