Muhammad Shoaib Farooq

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About

Muhammad Shoaib Farooq is a researcher at the forefront of pattern recognition and cybersecurity, whose work bridges the gap between human-computer interaction and digital defense. His primary research areas include facial emotion recognition (FER) under challenging conditions and machine learning applications for malware detection. Farooq’s most notable contribution is his pioneering study on emotion detection from facial expressions involving occlusions and tilt—a critical advancement for real-world surveillance, activity recognition, and stress analysis systems. This work, published in 2022, has already garnered 21 citations, reflecting its timely relevance to fields like home automation and computer games. In parallel, Farooq has systematically explored the role of logistic regression in malware detection, addressing the escalating security threats in networked systems—from banking to robotics and online social life. His systematic literature review, though early in its citation journey with 3 citations, underscores his commitment to foundational cybersecurity challenges. By tackling both the human and technical dimensions of intelligent systems, Farooq demonstrates a versatile research portfolio that promises to shape safer, more responsive technologies for an increasingly connected world.