I am a Ph.D. student in the Kim Jaechul Graduate School of AI at KAIST, where I am advised by Prof. Kijung Shin at Data Mining Lab. I received my B.S. in Computer Science and Engineering from Sungkyunkwan University. I worked at Amazon as an Applied Scientist Intern in 2022 and at NEC Labs America as a Research Intern in 2023. My research interests include data mining, machine learning, and social network analysis.
Education
Korea Advanced Institute of Science and Technology (KAIST) Sep. 2020 - Present (Seoul, South Korea)
M.S. & Ph.D. in Artificial Intelligence
M.S. & Ph.D. in Artificial Intelligence
Sungkyunkwan University (SKKU) Mar. 2016 - Aug. 2019 (Suwon, South Korea)
B.S. in Computer Science and Engineering
B.S. in Computer Science and Engineering
Work Experience
NEC Labs America May 2023 - Aug. 2023 (Princeton, USA)
Research Intern
Research Intern
Amazon Sep. 2022 - Dec. 2022 (San Francisco, USA)
Applied Scientist Intern
Applied Scientist Intern
Publications
[P1] A Survey on Hypergraph Mining: Patterns, Tools, and Generators
- Geon Lee*, Fanchen Bu*, Tina Eliassi-Rad, and Kijung Shin
- arXiv (2024)
[J6] Representative and Back-in-Time Sampling from Real-World Hypergraphs
- Minyoung Choe, Jaemin Yoo, Geon Lee, Woonsung Baek, U Kang, and Kijung Shin
- Transaction on Knowledge Discovery from Data (TKDD) (2024)
- pdf | shorter ver. | code
[C9] VilLain: Self-Supervised Learning on Homogeneous Hypergraphs without Features via Virtual Label Propagation
- Geon Lee, Soo Yong Lee, and Kijung Shin
- The Web Conference (WWW), 2024
- pdf | code
[T2] Mining of Real-World Hypergraphs: Patterns, Tools, and Generators
[J5] Random Walk with Restart on Hypergraphs: Fast Computation and an Application to Anomaly Detection
[J4] Hypergraph Motifs and Their Extensions Beyond Binary
- Geon Lee*, Seokbum Yoon*, Jihoon Ko, Hyunju Kim, and Kijung Shin
- The VLDB Journal (2023)
- pdf | shorter ver. | code
[J3] Hypercore Decomposition for Non-Fragile Hyperedges: Concepts, Algorithms, Observations, and Applications
[J2] Temporal Hypergraph Motifs
- Geon Lee and Kijung Shin
- Knowledge and Information Systems (KAIS) (2023)
- pdf | shorter ver. | code
[T1] Mining of Real-World Hypergraphs: Patterns, Tools, and Generators
[C8] Set2Box: Similarity Preserving Representation Learning for Sets
- Geon Lee, Chanyoung Park, and Kijung Shin
- IEEE International Conference on Data Mining (ICDM), 2022
- pdf | longer ver. | slides | code
[C7] HashNWalk: Hash and Random Walk Based Anomaly Detection in Hyperedge Streams
[C6] MiDaS: Representative Sampling from Real-World Hypergraphs
[J1/W1] Simple Epidemic Models with Segmentation Can Be Better than Complex Ones
[C5] THyMe+: Temporal Hypergraph Motifs and Fast Algorithms for Exact Counting
- Geon Lee and Kijung Shin
- IEEE International Conference on Data Mining (ICDM), 2021
- pdf | longer ver. | slides | code
- Selected as one of the best-ranked papers of ICDM 2021
[C4] How Do Hyperedges Overlap in Real-World Hypergraphs? - Patterns, Measures, and Generators
[C3] Hypergraph Motifs: Concepts, Algorithms, and Discoveries
- Geon Lee, Jihoon Ko, and Kijung Shin
- International Conference on Very Large Data Bases (VLDB), 2020
- pdf | appendix | longer ver. | slides | code
[C2] MEGA: Multi-View Semi-Supervised Clustering of Hypergraphs
- Joyce Jiyoung Whang, Rundong Du, Sangwon Jung, Geon Lee, Barry Drake, Qingqing Liu, Seonggoo Kang, and Haesun Park
- International Conference on Very Large Data Bases (VLDB), 2020
[C1] Hyperlink Classification via Structured Graph Embedding
- Geon Lee, Seonggoo Kang, and Joyce Jiyoung Whang
- ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2019
Academic Services
Program Committee
- SIAM International Conference on Data Mining (SDM), 2024
- AAAI Conference on Artificial Intelligence (AAAI), 2024
- Learning on Graphs Conference (LoG), 2022 - 2023
- ACM International Conference on Information and Knowledge Management (CIKM), 2022
- The Web Conference (WWW), 2024
- ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023 - 2024
- Big Data Research (2024)
- IEEE Transactions on Knowledge and Data Engineering (TKDE) (2023)
- IEEE Transactions on Neural Networks and Learning Systems (TNNLS) (2023)
- The VLDB Journal (2023)
Awards & Honors
Selected as One of the Best-Ranked Papers of ICDM 2021 Dec. 2021Sungkyunkwan Presidential AwardAug. 2019
Dean's List2016 - 2019
Sungkyun Software Scholarship (Full tuition for all semesters)2016 - 2019
Projects
AI-Based Weather Forecast Support DevelopmentJuly 2021 - PresentCOVID-19 Task ForceMar. 2020 - Sep. 2020
Teaching
KAIST AI506 Data Mining and SearchSpring 2021, Spring 2023KAIST AI607 Graph Mining and Social Network AnalysisFall 2020, Fall 2021, Fall 2022, Fall 2023
KAIST AI617 Machine Learning for RoboticsSpring 2022
SKKU CSE3036 Seminar in Computer EngineeringFall 2019