Scholar
Changhee Lee
Google Scholar ID: kSvJTg4AAAAJ
Assistant Professor, Korea University
Citations & Impact
Citations
1,994
H-index
18
i10-index
26
Publications
20
Co-authors
14
list available
Contact
Publications
Resume (English only)
Academic Achievements
- November 2025: Paper on risk prediction of major adverse cardiovascular events accepted by JMIR Medical Informatics.
- October 2025: Won 3rd place in the 2025 IEEE Transactions on Biomedical Engineering Best Paper Awards.
- July 2025: Paper on contrastive learning for text-image retrieval accepted by Applied Intelligence.
- May 2025: Paper on active feature acquisition accepted by ICML 2025.
- January 2025: Paper using NLP to predict risk in the pediatric ER accepted by Scientific Reports.
- September 2024: Paper on contrastive learning-based survival analysis accepted by NeurIPS 2024.
- July 2024: Paper on group-sparse feature selection method accepted by IEEE Access.
- July 2024: Paper on domain-agnostic anomaly detection accepted by CIKM 2024.
- May 2024: Paper on synergistic feature selection accepted by ICML 2024.
- January 2024: Paper on time-series imputation accepted by ICLR 2024.
- January 2024: Paper on Predictive HO with Time-series Forecasting accepted by IEEE Network Magazine (Impact Factor: 9.6).
- September 2023: Paper on active sensing under cost pressure accepted by NeurIPS 2023.
- April 2023: Paper on time-series forecasting using SDEs accepted by ICML 2023.
Research Experience
- Leading the Actionable Intelligence Lab's research team, focusing on solving real-world problems in healthcare, manufacturing, and other critical decision-making areas. Involved in multiple research projects, including risk prediction, time-series analysis, feature selection, and more.
Education
- Starting September 2024, Assistant Professor in the Department of Artificial Intelligence at Korea University.
Background
- Research Interests: Developing cutting-edge machine learning and artificial intelligence theories and methods, including self- and semi-supervised learning, causal inference, automated ML, and more. Professional Field: Healthcare, manufacturing, and other domains where critical decision making is key.
Miscellany
- Personal interests and hobbies not mentioned.
