Jahanzaib Shabbir

Institute for Systems Engineering and Computers

Papers

Total Citations

H-Index

About

Jahanzaib Shabbir is a researcher whose work sits at the compelling intersection of deep learning, robotics, and medical technology. His research has made meaningful contributions to two interconnected domains: the application of artificial intelligence in robotic systems and the advancement of minimally invasive medical technologies. Among his most notable contributions is a 2017 study exploring deep learning-based sensor fusion for endoscopic capsule robots, which has garnered 36 citations. This work addressed a critical challenge in capsule endoscopy — reliable real-time localization — by combining RGB camera data with magnetic localization information, pushing forward the frontier of gastrointestinal diagnostics and therapeutics. His ability to translate cutting-edge AI techniques into practical medical applications reflects both technical depth and clinical awareness. Shabbir also authored a widely referenced 2018 survey on deep learning techniques for mobile robot applications, accumulating 26 citations, demonstrating his command of the broader robotics landscape. This comprehensive review has served as a valuable resource for researchers navigating the promises and challenges of integrating deep neural networks into autonomous systems. Collectively, his work positions him as a thoughtful contributor bridging intelligent systems and real-world robotic applications.