Mohibullah Khan

NFC Institute of Engineering and Technology

Papers

Total Citations

H-Index

About

Mohibullah Khan is a rising researcher in the field of computer vision and cybersecurity, with a focused interest in biometric authentication and anti-spoofing technologies. His most cited work, "A Novel Face Spoofing Detection Using Handcrafted MobileNet" (2023), addresses a critical vulnerability in facial recognition systems—a technology now ubiquitous in domains ranging from human-robot interaction and commercial services to political security. Khan’s contribution lies in bridging the gap between lightweight, efficient neural architectures (MobileNet) and traditional handcrafted feature extraction, offering a practical solution for real-time spoofing detection without sacrificing accuracy. While his citation count is still growing, the timeliness of his research underscores its relevance as face recognition systems become increasingly embedded in everyday life. By tackling the persistent challenge of presentation attacks, Khan is helping to fortify the trustworthiness of biometric systems. His work signals a promising trajectory in applied machine learning, where the balance between computational efficiency and robust security is paramount. For students and researchers exploring adversarial robustness or edge-device AI, Khan’s approach offers a compelling case study in pragmatic innovation.