Sandeep Chand Kumain

Sandeep Chand Kumain

Assistant Professor

Profile Summary

Sandeep Chand Kumain earned his Ph.D. in Computer Science and Engineering from National Institute of Technology Uttarakhand. Specializing in computer vision, image processing, and deep learning, his research aligns with the cutting-edge demands of modern computing.

He is proficient in programming languages including C, Java, and Python. With more than 20 research publications in reputed international journals and conferences, he has established a strong academic presence.

His current work focuses on AI, machine learning, and deep learning, with active interest in collaborative research related to saliency detection in images and videos, image and video noise handling, and broader computer vision challenges.

Work Experience

Sandeep Chand Kumain has been associated with UPES since May 2024 as an Assistant Professor. Prior to joining UPES, he was engaged in doctoral research at National Institute of Technology Uttarakhand.

His academic journey reflects a strong commitment to research, innovation, and teaching excellence.

Research Interests

Deep Learning | Machine Learning | Computer Vision | Image Processing | Visual Saliency Detection | Video Analytics | Artificial Intelligence

Teaching Philosophy

His teaching philosophy centers on project-based learning, where students gain deeper understanding by applying concepts to real-world problems. He believes learning is most effective when it is hands-on, collaborative, and exploratory.

Through practical projects, he encourages students to think critically, innovate, and develop technical as well as teamwork skills. His goal is to nurture independent, industry-ready learners capable of contributing confidently to evolving technological fields.

Courses Taught

Data Structures | Operating Systems | Design and Analysis of Algorithms | C Programming

Scholarly Activities

He has contributed to more than 20 high-quality research publications, including papers in esteemed international journals such as ACM Computing Surveys. His research primarily focuses on visual saliency detection, alongside broader contributions to computer vision, image processing, and deep learning.

He continues to explore advanced AI methodologies for image understanding, noise reduction, and intelligent visual systems.