Gi-Cheon Kang

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About

Gi-Cheon Kang is a rising researcher in embodied AI and human-robot interaction, with a focus on enabling robots to understand and execute natural language instructions in dynamic environments. His work spans three key areas: language-guided robotic manipulation, interactive object grasping, and embodied instruction following. Kang’s major contributions include pioneering lifelong learning for visual grounding in robotic manipulation (GVCCI, 2023), which allows robots to adapt to new environments without retraining, and developing pragmatic communication models for object grasping (PROGrasp, 2024) that improve human-robot dialogue efficiency. His Socratic Planner (2025) introduces a zero-shot planning method using self-question-answering, eliminating the need for supervised training in compositional task planning. With over 13 citations across his most-cited papers, Kang’s work is gaining traction for its practical approach to bridging language understanding and robotic action. Notably, his research emphasizes real-world applicability, addressing challenges like environment adaptation and efficient human-robot communication, making him a promising voice in the future of interactive robotics.