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Dr. Vivek Kumar Yadav
Assistant Professor
Profile Summary
Dr. Vivek Kumar Yadav is an academician and researcher specializing in medical image processing. He earned his Ph.D. and M.Tech. from NIT Bhopal. His research interests span computer vision, image processing, deep learning, machine learning, and image captioning. His work focuses on improving early-stage diagnosis of lung diseases by enhancing low-contrast chest X-ray images and developing effective lung segmentation techniques to support more accurate classification. Dr. Yadav is dedicated to creating affordable, accessible diagnostic systems for use in remote areas to improve healthcare outcomes.
Work Experience
Dr. Vivek Kumar Yadav recently joined UPES as a faculty member, where he currently teaches Design Analysis and Algorithms along with the Linux Lab. Before joining UPES, he served as a Teaching Assistant (TA) at NIT Bhopal for four years, contributing to courses such as the Image Processing Lab using Python and Network Analysis. Prior to this, he gained valuable industry experience as a Content Researcher at Embibe Indiavidual Learning Ltd. in Bengaluru.
Research Interests
Medical Image Processing, Deep Learning, Machine Learning, Computer Vision, and Image Captioning.
Teaching Philosophy
Dr. Vivek Kumar Yadav believes in a hands-on, application-oriented approach that encourages students to engage deeply with real-world problems. His goal is to create an environment where students develop both strong technical foundations and the confidence to innovate.
Courses Taught
Dr. Vivek Kumar Yadav is currently assigned the following courses
Scholarly Activities
Dr. Vivek Kumar Yadav has published impactful research in reputed SCIE journals such as MBEC, MTAP, and IETE Technical Review, with a strong focus on computer vision. He has presented his work at international conferences hosted by esteemed institutions like MANIT Bhopal, including studies on transfer learning methods for semantic segmentation. In addition, he has mentored both undergraduate and postgraduate students on research projects involving computer memory, image processing and deep learning techniques.
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