Human-centered intelligent systems
Human–AI Skill Learning through Multimodal Sensing and Embodied Intelligence
I am a Ph.D. candidate at the Human-Centered Intelligent Systems Lab at the Gwangju Institute of Science and Technology, advised by Prof. SeungJun Kim.
I study how physical skills can be captured from human demonstrations, represented computationally, and transformed into adaptive feedback for human learning. My work combines multimodal sensing, XR/MR, and human–AI interaction to understand movement, performance, and learning state.
Racket sports serve as my primary testbed, spanning multimodal datasets, performance modeling, and adaptive motion guidance.
My long-term goal is to connect physical-skill data collection, computational representation, and interactive feedback in systems that help people learn complex motor skills.
My broader collaborative work applies the same sensing-and-adaptation perspective to accessibility, mobility, and immersive interaction.
Research trajectory
Selected Publications
Seven selected works tracing my research from multimodal human sensing to adaptive and embodied systems.
IMPACT: Exploring Integrated Muscle-Posture AR Coaching in Static-Stance Badminton Training
SSRN Preprint
An AR coaching system that integrates expert-aligned motion replay with synchronized EMG feedback for static-stance badminton practice.
Tell Me When It Feels Right: LLM-Mediated Challenge Regulation for Physical Self-Training in Badminton
SSRN Preprint
An LLM-mediated coaching system that interprets physiological, subjective, and textual signals to regulate challenge in badminton self-training.
ErgoPulse: Electrifying Your Lower Body With Biomechanical Simulation-Based Electrical Muscle Stimulation Haptic System in Virtual Reality
Proceedings of the CHI Conference on Human Factors in Computing Systems
Award: Honorable Mention Award
A biomechanical-simulation-driven electrical muscle stimulation haptic system for virtual reality.
Adaptive Walker: User Intention and Environmentally Aware Intelligent Walker with High-Resolution Tactile and IMU Sensor
IEEE International Conference on Robotics and Automation (ICRA)
Multimodal intention and environment sensing for an intelligent mobility-assistance platform.
Education
Last updated: 2026-07-21