Yeonju Lee
Knowledge-Informed Machine Learning for Complex Systems
I develop learning methods that integrate domain and scientific knowledge to improve reliability under limited data and changing environments.
Applications: Healthcare · Precision Agriculture
CVLast updated Sep, 2026 · Google Scholar · Email · LinkedIn
Research Areas
Representation
Knowledge-guided representation learning
Domain and anatomical knowledge for learning from limited and heterogeneous scientific data.
Representative paper Oral-Anatomical Knowledge-Informed Semi-Supervised Learning for 3D Dental CBCT Segmentation and Lesion Detection
Reasoning
Knowledge-grounded scientific reasoning
Foundation models that use scientific knowledge to interpret complex spatiotemporal patterns.
Representative paper SPADE: A Large Language Model Framework for Soil Moisture Pattern Recognition and Anomaly Detection in Precision Agriculture
Decision & Control
Reliable learning-enabled decision-making
Knowledge-informed learning for robust decisions under changing physical environments.
Current work Knowledge-informed control under distribution shift