Muhammad Haris

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About

Muhammad Haris is a researcher whose work sits at the dynamic intersection of artificial intelligence, autonomous systems, and intelligent transportation. His research focuses on optimization algorithms and their application to smart mobility challenges, particularly path planning for autonomous and intelligent vehicles. His most notable contribution to date is his 2024 work introducing a fast-converging Distance-Dependent Particle Swarm Optimization (PSO) algorithm tailored for smart vehicle path planning — a study that has already garnered 24 citations within its publication year, signaling rapid uptake by the research community. This work addresses a well-recognized bottleneck in the PSO framework: slow convergence and inefficiency in complex, real-world navigation environments. By developing a distance-dependent variant, Haris advances the field of metaheuristic optimization in ways directly applicable to robotics, autonomous driving, and intelligent transportation systems. His contributions reflect a broader commitment to bridging theoretical algorithmic innovation with practical engineering solutions. Researchers working in autonomous systems, swarm intelligence, or smart mobility will find his work a valuable and timely reference as these fields continue to accelerate rapidly.