Kamran Abid

NFC Institute of Engineering and Technology

Papers

Total Citations

H-Index

About

Kamran Abid is a rising researcher at the intersection of assistive technology and computer vision, with a focus on deep learning applications for human-robot interaction. His most impactful work, “Robot Assist Sign Language Recognition for Hearing Impaired Persons Using Deep Learning” (2023, 13 citations), addresses a critical societal need by developing systems that bridge communication gaps between the deaf community and hearing individuals. This contribution stands out for its practical integration of robotics and AI to enable real-time sign language translation, directly improving accessibility. Abid also explores security in human-robot systems through his work on face spoofing detection, where he proposed a novel hand-crafted MobileNet architecture (2023, 3 citations) to combat presentation attacks in applications ranging from robotics to biometrics. While his citation counts are modest, his research demonstrates a clear commitment to socially impactful AI, particularly in assistive robotics and trustworthy human-machine interaction. His work signals a promising trajectory in creating more inclusive and secure autonomous systems.