Naeem Aslam

NFC Institute of Engineering and Technology

Papers

Total Citations

H-Index

About

Naeem Aslam is a rising researcher at the intersection of computer vision, human-robot interaction, and assistive technology. His work focuses on bridging communication gaps through deep learning, with a particular emphasis on sign language recognition and biometric security. In his highly cited 2023 study, "Robot Assist Sign Language Recognition for Hearing Impaired Persons Using Deep Learning," Aslam developed a system to facilitate seamless interaction between the deaf community and hearing individuals, leveraging deep neural networks to interpret sign language in real time—a contribution that has already garnered 13 citations. He further advanced the field of secure human-robot communication with his work on "A Novel Face Spoofing Detection Using Handcrafted MobileNet," which addresses vulnerabilities in facial recognition systems used across commercial, hospitality, and political domains. By integrating handcrafted features with lightweight MobileNet architectures, Aslam has proposed more robust anti-spoofing measures. Though early in his career, his research demonstrates a clear commitment to making technology more inclusive and secure, positioning him as a promising voice in applied deep learning for social good.