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About

Muhammad Marwan’s research lies at the intersection of nonlinear dynamics, chaos theory, and intelligent robotics, with growing contributions to biomedical image processing. His work on hyperjerk chaotic systems—introducing a novel modification using a hyperbolic sine nonlinearity—has advanced the understanding of complex dynamical behaviors and their synchronization, with direct applications in chaotic mobile robot navigation. His 2020 paper on this topic has garnered 28 citations, while his observer-based control framework for quadrotor chaotic systems (21 citations) demonstrates the practical utility of chaos theory in real-world robotics. More recently, Marwan has extended his expertise into healthcare, developing a dental image enhancement network to improve early diagnosis of oral diseases (17 citations, 2023), addressing critical challenges in intelligent dentistry. His innovative designs, such as the nest-fold system via dual-route fractal processes and mixed obstacle avoidance in chaotic mobile robots, showcase his ability to translate theoretical chaos into functional robotic systems. With a growing portfolio of highly cited work, Marwan is establishing himself as a versatile researcher who bridges fundamental nonlinear dynamics with impactful engineering and medical applications.