Jasni Mohamad Zain

Universiti Malaysia Pahang Al-Sultan Abdullah, Universiti Teknologi MARA System

Papers

Total Citations

H-Index

About

Jasni Mohamad Zain is a researcher whose work bridges the critical intersection of cybersecurity, artificial intelligence, and human-robot interaction. Her primary research areas include machine learning for network anomaly detection, workplace safety automation, and the application of non-linear mathematical models to security challenges. In her most-cited work, "Machine Learning Techniques for Detecting Anomalies in IoT Networks" (2023, 6 citations), she explores how advanced algorithms can identify irregular patterns in increasingly vulnerable Internet of Things ecosystems—a contribution that addresses the growing need for robust, automated cybersecurity defenses. Her second notable paper, "Security robot for the prevention of workplace violence using the Non-linear Adaptive Heuristic Mathematical Model" (2021, 3 citations), tackles the pressing issue of human-machine safety in Industry 4.0 environments. This work proposes an innovative robotic security system designed to prevent workplace violence, demonstrating her commitment to applying theoretical models to real-world safety challenges. While her citation counts are still developing, Zain's research shows promise in shaping safer, more intelligent technological systems. Her focus on practical, interdisciplinary solutions—from IoT security to collaborative robotics—positions her as an emerging voice in the fields of computer science and engineering, particularly for students and researchers interested in the convergence of AI, security, and human-centered automation.