CHUNGNAM NATIONAL UNIVERSITY
Data Intelligence Lab
We are the Data Intelligence Lab (DILAB) at the Department of Computer Science and Engineering, Chungnam National University, Korea 🇰🇷. Our research focuses on graph machine learning, trustworthy AI, recommender systems & IR, and GraphRAG & LLMs.
🔬 Research
Graph Machine Learning
Representation learning and machine learning for complex graph-structured data.
Trustworthy AI
Fairness, uncertainty quantification, and reliability of machine learning models.
Recommender Systems & IR
Learning and retrieval methods for personalized and knowledge-rich information systems.
GraphRAG & LLMs
Graph-enhanced retrieval, reasoning, and knowledge augmentation for large language models.
🔥 News
2026.09
🎉 Our paper on traffic forecasting robust to aperiodicity
was accepted to NeurIPS 2026.
2026.08
🎉 Our paper on few-shot learning on text-attributed graphs
was accepted to CIKM 2026.
2026.08
🎓 Congratulations to Soyoung on completing her Ph.D.!
2026.07
🎉 Our paper on uncertainty quantification for GNNs
was presented at ICML 2026.
2026.07
🎉 Two papers on GraphRAG and
recommendation were presented at SIGIR 2026.
2026.03
🎉 Our paper on visual token pruning for multimodal LLMs
was presented at WACV 2026.
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2026.02
🎉 Our paper on LLM-enhanced graph representation learning
was presented at WSDM 2026.
2026.02
🎓 Congratulations to Jongmin on completing his Ph.D.
and Hyewon on completing her M.S.!
2025.11
🏆 DILAB placed 4th and received a Special Award
in the CIKM 2025 AnalytiCup Alibaba Challenge.
2025.11
🏆 DILAB won 2nd Place in the
ScienceON AI Challenge 2025.
2025.11
🎉 Two papers on fair graph learning and
signed community detection were presented at CIKM 2025.
2025.08
🎓 Congratulations to Soohwan and Jeongseon
on completing their Ph.D. degrees!
2025.06
🎉 Our paper on zero-shot industrial anomaly segmentation
was presented at PAKDD 2025.
2025.03
🎉 Our paper on in-context learning in text-attributed graphs
was presented at EDBT 2025.
2025.02
🎓 Congratulations to Hwan on completing his Ph.D.
and Mingyu on completing his M.S.!
📢 Join Us
We welcome motivated students interested in learning from complex and structured data,
from fundamental methods to real-world applications.
We currently have openings for M.S. and Ph.D. students.
To apply, please send your CV with a brief introduction and motivation to
Prof. Sungsu Lim
at sungsu@cnu.ac.kr.
For research collaborations, feel free to reach out as well.