Computer Science & Engineering and Information Technology (CSE&IT)

Ajeet Kumar Verma is an Assistant Professor in the Department of Computer Science and Engineering/Information Technology at Jaypee University of Information Technology (JUIT), Solan, India. He is an accomplished researcher and educator with expertise spanning computer vision, deep learning, image and video super-resolution, quality assessment, and test-time adaptation.

He is currently pursuing his Ph.D. in Computer Science and Engineering at the Indian Institute of Technology (IIT) Jammu, where he maintains a strong academic record (CGPA: 8.25/10). His doctoral research, titled “Adaptive Super-Resolution and Quality Assessment via Test-Time Adaptation,” focuses on developing adaptive learning frameworks for real-world image and video super-resolution, with particular emphasis on perceptual quality assessment. His thesis was submitted in January 2026.

Mr. Verma earned his M.Tech. in Computer Science and Engineering from Babasaheb Bhimrao Ambedkar University, Lucknow, and his B.Tech. in Information Technology from Dr. A.P.J. Abdul Kalam Technical University (formerly UPTU), Lucknow. His strong foundation in mathematics, algorithms, and programming has consistently supported his interdisciplinary research.

Before joining JUIT, he served as a Junior Research Fellow at IIT Jammu, Senior Research Fellow at IIT Goa, and Junior Research Fellow at NIT Goa, contributing to several high-impact, government-funded research projects supported by DST-SERB, Government of India, and international collaborators such as INRIA, France. His work includes rainfall forecasting for India using novel deep learning architectures, malaria incidence prediction using spiking neuron models, and intelligent hardware design for cyber-physical systems.

Mr. Verma’s research contributions in computer vision and video processing are widely recognized. He has published in top-tier journals and conferences, including IEEE Transactions on Artificial Intelligence, CVPR Workshops, ICME, ICASSP, and Frontiers in Bioscience. His work on real-world video quality assessment and super-resolution via test-time adaptation has gained particular attention, along with his contributions to perceptual loss functions and adaptive quality-aware models.

He has actively participated in prestigious international challenges, securing Rank 2 at ICME 2025 Grand Challenge, Rank 2 at IEEE ICASSP 2023 Drone-vs-Bird Challenge, and ranking among top solutions in the NTIRE 2025 Challenge at CVPR. These achievements highlight his ability to translate theoretical research into competitive, real-world solutions.

In addition to research, Mr. Verma is deeply committed to teaching and mentoring. His teaching portfolio includes Software Development Fundamentals, Competitive Programming, Data Analytics using R and Python, and Software Engineering, with a strong emphasis on practical skills, algorithmic thinking, and industry relevance.

He is a UGC-NET qualified Junior Research Fellow and Assistant Professor (CSE) and actively contributes to the academic community through conference volunteering, workshops, and institutional responsibilities.