Zeeshan Nisar

I am Zeeshan Nisar, currently enrolled as a Ph.D. Researcher at SDC, ICube (Laboratory of Engineering Sciences, Computing and Imaging, UMR7357) at the University of Strasbourg, France. The registered topic for my thesis is "Self-regularized deep learning in the presence of limited data for Medical Imaging" under the supervision of Dr Thomas Lampert.

Having a working experience of more than 03 years in the Artificial Intelligence domain, I have held various research positions at the Medical Imaging and Diagnostic (MID) Lab at COMSATS University Islamabad, Pakistan, and at Experts Vision, Islamabad, Pakistan. The MID Lab is a part of the National Center of Artificial Intelligence (NCAI), a major project of the Higher Education Commission of Pakistan which aims to provide Computer-Aided Diagnosis (CAD) systems to diagnose and detect cancerous regions for Lungs, Brain, and Breast. My research interest lies in the field of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) to solve real-world applications related to Computer Vision (CV) and Medical Imaging.

I hold my Master’s Degree in Computer Science from COMSATS University Islamabad, Pakistan with a 3.73/4.00 CGPA. During my Master's period, I have proposed a novel approach for Weakly-supervised Segmentation (WSS) of Tuberculosis Infected Regions using state of the art Generative Adversarial Networks. This approach is introduced to detect the infectious region of Tuberculosis at pixel-level using weak labels. We have also formatted this novel approach with another modified version of its in a paper as "Counterfactual Explanation and Instance-Generation using Cycle-Consistent Generative Adversarial Networks" and have submitted the manuscript to the highly reputed Information Fusion Journal. My research interest includes Artificial Intelligence, Machine Learning, Deep Learning in the domain of Medical Imaging and Computer Vision.

You can find more information about my various projects at my GitHub Profile.