In‐Geol Choi

Papers

Total Citations

H-Index

About

In-Geol Choi is a researcher at the forefront of human–machine interaction and intelligent sensing systems, with a particular focus on wearable technologies and machine learning applications. His most cited work, "Object classification system using temperature variation of smart finger device via machine learning" (2023, 10 citations), introduces a novel approach to tactile sensing by leveraging thermal dynamics captured through a smart finger device. This contribution demonstrates how subtle temperature changes during contact can be classified using machine learning algorithms, enabling object recognition without traditional visual or pressure-based sensors. Choi’s research bridges the gap between material science and artificial intelligence, offering promising pathways for prosthetics, robotics, and assistive technologies. Though early in his career, his work has already garnered attention for its originality and practical potential, laying a foundation for more intuitive, sensor-rich interfaces. By reimagining how devices perceive their environment through thermal cues, Choi is helping to shape the next generation of smart, context-aware systems.