Shivam Gangwar

I hold a PhD in Electronics and Communication Engineering from Kurukshetra University with my thesis focused on Chest X ray Image Processing and Deep Learning in Healthcare. I also completed an MSc in Electronics from CSJM University Kanpur and a BSc Honours in Electronic Science from Hansraj College University of Delhi. My research interests include medical imaging, deep learning and blockchain technology.

My research experience includes working as a Junior Research Fellow from 2023 to 2025 under a DST SERB funded project titled New Modified Histogram Equalization Based Contrast Enhancement Method and Automated Deep Learning Based Identification System for COVID 19 X Ray Images. In this role I developed and implemented algorithms for image enhancement and classification, resulting in multiple publications in reputed journals such as Scientific Reports Nature, Biomedical Signal Processing and Control Elsevier, and Soft Computing Springer.

I have also gained international exposure through research visits to Universiti Sains Malaysia in 2023 and Mahidol University Bangkok in 2024. At these institutions I collaborated on projects involving image contrast enhancement and deep learning models for COVID 19 diagnosis. These experiences improved my ability to handle noisy real world data and to work in interdisciplinary international research teams.

In addition to my research work I have served as a Teaching Assistant at Kurukshetra University where I taught courses such as Blockchain Technology, Image Processing, Data Structures and Analog Communication. I also serve as a reviewer for Biomedical Signal Processing and Control Elsevier, reflecting recognition of my expertise by the global scientific community.

I have qualified GATE 2023 and UGC NET in Electronic Science in 2021 and 2022, and I was awarded the DST Inspire Scholarship in 2015 along with provisional selection for the Inspire Fellowship in 2021. My technical skills include programming in Python C and C++, use of deep learning frameworks such as TensorFlow PyTorch and Keras, and experience with MATLAB and OpenCV for image processing.