Gang Hu

Papers

Total Citations

H-Index

About

Dr. Gang Hu is a leading figure in the development of advanced metaheuristic optimization algorithms, with a particular focus on bio-inspired and physics-inspired computing. His research centers on designing novel swarm intelligence techniques and enhancing existing algorithms to solve complex, real-world engineering problems, such as smooth path planning and multi-domain optimization. Dr. Hu’s most impactful contributions include the creation of the Hierarchical Guided Slime Mould Algorithm (HG-SMA), which achieved 47 citations for its innovative approach to path planning, and the enhanced Kepler Optimization Algorithm (CGKOA), which garnered 38 citations for its robust performance across diverse optimization challenges. These works demonstrate his ability to systematically improve algorithm convergence, exploration, and exploitation. With a growing citation record, Dr. Hu’s research is shaping the next generation of optimization solvers, making him a valuable resource for students and researchers interested in computational intelligence and its applications in robotics, engineering design, and beyond.