Chi‐Man Pun

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About

Chi-Man Pun is a leading researcher in swarm intelligence and robotics, best known for his innovative work in optimizing artificial bee colony (ABC) algorithms for real-world applications. His major contributions include developing a global best guided artificial bee colony algorithm that significantly enhances robot path planning, achieving 94 citations for its breakthrough approach to solving complex navigation problems. Pun also introduced an improved ABC algorithm incorporating an elite search strategy, which accelerates convergence speed and strengthens local search capabilities—a critical advancement for robot vision systems. His research bridges theoretical optimization with practical robotics, demonstrating how bio-inspired algorithms can tackle challenges in autonomous navigation and visual perception. With a focus on enhancing algorithm efficiency and robustness, Pun’s work has become foundational for researchers exploring swarm-based solutions in engineering. His achievements highlight the power of combining computational intelligence with mechanical systems, offering students and researchers a compelling model for applying metaheuristic methods to cutting-edge technological problems.