Lee, Ki-chun
Hanyang University
研究室紹介
Professor Lee, Ki-chun's research lab specializes in intelligent systems and data-driven methodologies, focusing on the integration of affective computing and advanced machine learning for real-time human-computer interaction. The lab explores emotion recognition through multimodal signals—particularly facial and audio cues—to enhance user engagement in interactive environments such as exhibitions and smart services. A key research direction involves developing robust, scalable machine learning models, including ensemble techniques like AdaBoost.RMU.R, for handling large-scale data in practical applications. The lab also emphasizes the application of computational intelligence in service innovation and human-centered technology design.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
2Both researchers and practitioners are showing an increased interested in interactive exhibition services. Interactive exhibition services are designed to directly respond to visitor responses in real time, so as to fully engage visitors’ interest and enhance their satisfaction. In order to install an effective interactive exhibition service, it is essential to adopt intelligent technologies that enable accurate estimation of a visitor’s emotional state from responses to exhibited stimulus. Stud
The purpose of this study is to challenge a computational regression-type problem, that is handling large-size data, in which conventional metamodeling techniques often fail in a practical sense. To solve such problems, regression-type boosting, one of ensemble model techniques, together with bootstrapping-based re-sampling is a reasonable choice. This study suggests weight updates by the amount of the residual itself and a new error decision criterion which constructs an ensemble model of model