Papers
13
Total Citations
218
H-Index
7
About
Dr. Ji-Hyeong Han is a leading researcher in human-robot interaction (HRI) and evolutionary multiobjective optimization, with a career dedicated to enabling robots to understand and collaborate with humans. Her foundational work includes a highly cited (101 citations) preference-based solution selection algorithm for evolutionary multiobjective optimization, which addresses the critical challenge of decision-making from a set of nondominated solutions. Dr. Han has made significant contributions to robot cognition, pioneering methods for robots to read human intention using cognitive architectures inspired by the mirror-neuron system and hierarchical behavior knowledge networks. Her research on behavior hierarchy-based affordance maps (21 citations) allows robots to infer human goals by understanding object-related behaviors, directly advancing natural HRI. In multi-robot systems, she developed preference-based task allocation frameworks that balance competency and workload. Notably, her work extends to video captioning from egocentric and exocentric robot views (22 citations) and evolutionary footstep planning for humanoid robots, demonstrating a rare ability to bridge high-level decision-making with low-level robotic control. With over 200 total citations, Dr. Han’s research is shaping the future of socially intelligent robots capable of seamless, intuitive collaboration.
Research Focus
Key Achievements
Top Papers
- 1
- 2Evolutionary Multiobjective Footstep Planning for Humanoid Robots23 citations · 2010
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- 6A preference-based task allocation framework for multi-robot coordination10 citations · 2011
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- 8Prioritized Hindsight with Dual Buffer for Meta-Reinforcement Learning5 citations · 2022
- 9Market-Based Multiagent Framework for Balanced Task Allocation4 citations · 2013
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