Mr. Arpit Sharma

Assistant Professor

Mr. Arpit Sharma is an Assistant Professor and Computer Vision researcher, with his primary research area centered on designing advanced computer vision systems for visual perception, scene understanding, and real-time video analytics using deep learning. As an M.Tech Gold Medalist (GPA: 3.91/4), he combines strong theoretical foundations with practical expertise to build scalable, real-world AI solutions.

His research focuses on object detection, multi-object tracking, video analytics, and multimodal AI systems, with applications in smart surveillance, sports analytics, emotion-aware systems, and healthcare monitoring. He has authored 10+ peer-reviewed publications in reputed venues such as IEEE, Springer, and ACM, along with multiple patent filings in AI-based systems, reflecting a strong commitment to innovation and applied research.

In addition to research, he actively contributes to AI education and mentorship, delivering courses in Machine Learning, Deep Learning, Artificial Intelligence, and Data Science. He has guided numerous student projects in Computer Vision and Generative AI, emphasizing hands-on, research-driven learning.

His technical expertise includes PyTorch, TensorFlow, OpenCV, YOLO frameworks, Transformers, LangChain, and multimodal architectures, along with experience in building RAG pipelines, autonomous AI agents, and edge-deployable vision systems.

Arpit is particularly interested in advancing Computer Vision research at the intersection of vision-language models, real-time AI systems, and agentic frameworks that enable autonomous perception and decision-making in complex environments.