Research topics
Our research focuses on robust AI for imperfect data, explainable AI (XAI), and AI applications in biomedical and industrial domains. We develop machine learning methods that can learn reliably from noisy, incomplete, and complex real-world datasets such as biomedical data, medical images, and industrial process data.
Robust AI for Imperfect Data
Real-world datasets are often noisy, incomplete, and inconsistently labeled. Our research develops machine learning methods that remain reliable under such imperfect conditions. We study techniques for learning with label noise, missing data, and distribution shifts, with a focus on improving the robustness and generalization of AI models.
Explainable Artificial Intelligence (XAI)
As AI systems are increasingly used in high-stakes domains, understanding model decisions becomes essential. Our work explores interpretable and explainable machine learning methods that provide insights into model behavior, decision processes, and feature importance, enabling more transparent and trustworthy AI systems.
Biomedical AI and Medical Imaging
We develop AI methods for analyzing biomedical and clinical data, including medical images and molecular datasets. Our research aims to support biomedical discovery and clinical decision-making through robust predictive modeling, representation learning, and interpretable AI techniques.
Industrial AI and Process Optimization
Industrial systems generate large volumes of complex process data. Our research investigates data-driven methods for industrial process analysis, monitoring, and optimization. By integrating machine learning with domain knowledge, we aim to improve efficiency, reliability, and intelligent decision-making in industrial environments.
Open Positions | 학생 모집
We are looking for motivated undergraduate and graduate students interested in research in AI and data science. Students who are considering graduate study and want to gain research experience are especially encouraged to apply. Interested students please send a brief self-introduction to kimsu55@knu.ac.kr
AI 및 데이터 사이언스 연구에 관심 있는 학부생 및 대학원생을 모집합니다. 연구 경험을 쌓고 대학원 진학을 고려하는 학생들의 지원을 환영합니다. 관심 있는 학생은 간단한 자기소개와 함께 kimsu55@knu.ac.kr 로 연락 바랍니다.