Ki-Baek Lee

Korea Advanced Institute of Science and Technology

Papers

Total Citations

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About

Ki-Baek Lee is a pioneering researcher in multiobjective optimization and humanoid robotics, whose work bridges computational intelligence and real-world robotic control. His most impactful contribution, the 2013 paper on "Multiobjective Particle Swarm Optimization With Preference-Based Sort" (86 citations), introduces MOPSO-PS—a novel algorithm that integrates user preferences into particle swarm optimization to effectively balance competing objectives, such as stability and energy efficiency, in complex robotic tasks. This method has been applied to path-following footstep optimization for humanoid robots, demonstrating its practical utility in dynamic environments. Lee further advanced the field with his 2012 study on multi-objective evolutionary algorithm-based optimal posture control, which uses iterative linear quadratic regulators to generate disturbance-resistant trajectories while optimizing multiple performance criteria. Earlier in his career, he explored human-robot interaction through a 2007 paper on reflex and emotion-based behavior selection for toy robots, showcasing his versatility in designing socially engaging systems. With a total of 96 citations across his key works, Lee’s research has significantly influenced the development of intelligent, adaptive robots capable of operating in real-world scenarios, making him a notable figure in robotics and evolutionary computation.