Papers
3
Total Citations
33
H-Index
3
About
Ji Ho Kwak is a pioneering roboticist whose research lies at the intersection of semantic manipulation, human-robot interaction, and affective computing. His most impactful work, "Semantic Grasping Via a Knowledge Graph of Robotic Manipulation" (23 citations), introduces a graph representation learning approach that enables robots to reason about which gripper to use for specific tasks—moving beyond simple affordance-based grasping to truly task-aware manipulation. In "A Robot Capable of Proactive Assistance through Handovers for Sequential Tasks" (6 citations), Kwak advances human-robot collaboration by developing systems that understand human activities to offer timely, context-appropriate help. His innovative "Affect-driven Robot Behavior Learning System using EEG Signals" (4 citations) leverages brain-computer interfaces to decode user emotional states, allowing robots to learn from subconscious feedback and reduce negative feelings during interactions. By integrating knowledge graphs, proactive assistance, and affective learning, Kwak is shaping a future where robots not only perform tasks intelligently but also understand human intent and emotion, making them more intuitive and effective partners in shared environments.
Research Focus
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Top Papers
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