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MINDS Lab
About MINDS Lab 💻
We aim to advance Data Science (DS), Machine Learning (ML), and Artificial Intelligence (AI) technologies for the benefit of society by deepening the understanding of diverse data sources—including graph and hypergraph data, time-series data, heterogeneous data, streaming data, and multi-modal data—and by harnessing their unique properties. Our research interests includes, but not limited to, Graph Mining, Scalable Machine Learning, Time-Series Analysis, and Trustworthy AI
Graph Mining
Graph Mining
Graph/Hypergraph Representation Learning
Knowledge Graph Reasoning and Applications
Scalable Machine Learning
Scalable Machine Learning
Large-Scale Graph Database Engines
Distributed Machine Learning
Search & Recommendation
Search & Recommendation
Personalized Recommender Systems
Retrieval-Augmented Generation (RAG)
Time-Series Analysis
Time-Series Analysis
Time-Series Forecasting and Reconstruction
Multivariate Time-Series Anomaly Detection
Social Data Science
Social Data Science
Social Network Analysis and Mining
Mitigating Social and Political Polarization
Trustworthy AI
Trustworthy AI
Fairness and Explainability in AI Models
Machine Unlearning on Graphs
Joining Our Lab 👨🎓
We are looking for self-motivated and enthusiastic graduate students as well as undergraduate research interns. If you are interested in joining our team or have any inquiries, please reach out to us at yyko {@} cau.ac.kr with your CV and a brief introduction of yourself (including your research interests and motivation for joining our lab). Since we have limited slots for graduate students, we strongly encourage students to gain experience with our lab as research interns before applying.
(Updated: Aug, 2025) We currently do not have any available slots for graduate students in the Fall 2025 semester. Please check back next semester for availability.
News 🎉
📄 [2025.08] Two papers have been accepted in ACM CIKM 2025 [BKCSA 3] (one Full paper and one Short paper). Congratulation!
💻 [2025.04] Our lab started a new research project "Data-Centered Threshold Selection for Multivariate Tim-Series Anomaly Detection" (제어시스템 이상 탐지 모델을 위한 임계값 설정 방안 성능 분석 연구) with the National Security Research Institute (NSR) (국가보안기술연구소). Congratulation!
📄 [2025.01] Two papers have been accepted in WWW 2025 [BKCSA 4] (one Full paper and one Short paper). Congratulation!
📄 [2025.01] A paper has been accepted in IEEE TKDE [Q1: IF Top 1.8%]. Congratulation!
💻 [2024.10] Our lab started a new research project "Knowledge Hypergraph Learning and Reasoning for Real-World Applications" (실세계 응용을 위한 지식 하이퍼그래프 학습 및 추론 기술), supported by the National Research Foundation of Korea (NRF) (한국연구재단) (중견연구). Congratulation!💻 [2024.05] Our lab started a new research project "Performance Analysis of AI models for Time-Series Anomaly Detection according to Input Tags" (AI모델의 입력태그에 따른 제어시스템 이상탐지 성능분석 연구) with the National Security Research Institute (NSR) (국가보안기술연구소). Congratulation!
📄 [2024.03] A paper has been accepted in ACM CSCW 2024 [BKCSA 3]. Congratulation!
👏 [2024.03]. Dr. Yunyong Ko joined the School of Computer Science and Engineering at CAU.
Research Highlights ✨
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