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About

Hangyeol Kang is an emerging researcher at the intersection of social robotics, human-robot interaction, and affective computing. His work centers on developing intelligent robotic systems capable of nuanced, human-like engagement, with a particular focus on integrating large language models (LLMs) into socially interactive platforms. His most notable contribution to date is his involvement in the Nadine social robot project, which earned 18 citations within its first year of publication — a strong indicator of the work's resonance within the robotics and AI communities. This research demonstrated how LLMs can be leveraged to endow humanoid robots with affective capabilities and episodic memory, pushing the boundaries of what socially intelligent machines can achieve. Beyond social robotics, Kang has expanded his research portfolio into surgical AI, contributing to TransSG, a spatial-temporal transformer model for surgical gesture recognition — reflecting a versatile command of deep learning architectures. His more recent work on re-engagement dynamics in human-robot interactions brings a student-centered lens to understanding what sustains meaningful robot-human dialogue over time. Collectively, Kang's research positions him as a thoughtful contributor to the future of embodied AI and human-centered computing.