Mutaz M. Hamdan

King Fahd University of Petroleum and Minerals, New Generation University College

Papers

Total Citations

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About

Mutaz M. Hamdan’s research lies at the intersection of robotics, control systems, and artificial intelligence, with a focus on advancing the autonomy and security of complex robotic platforms. His work on mobile parallel manipulators (MPMs) provides foundational kinematic and dynamic models for hybrid robotic systems, solving positional and differential kinematics for multi-degree-of-freedom parallel robots mounted on wheeled mobile platforms. This contribution, published in 2013, has garnered 6 citations and remains a reference for researchers in mobile robotics and motion planning. More recently, Hamdan has pioneered the integration of deep learning into teleoperation systems. His 2022 paper on deep learning-based attack detectors for bilateral teleoperation systems (BTOS) addresses critical cybersecurity vulnerabilities in remotely controlled plants, where a human operator, master manipulator, and slave manipulator communicate over a network. This work, with 4 citations, demonstrates his ability to bridge robotics and AI for real-world safety. Hamdan’s research is notable for its dual focus on mechanical design and data-driven intelligence, making him a rising voice in secure, autonomous robotic systems.