About Me
I am an Assistant Professor in the School of Computer Science and Engineering at Chung-Ang University (CAU), where I am leading the Data Mining and Intelligence Systems (DMAIS) Lab.
Prior to joining CAU, I worked as a Postdoctoral Researcher at the Department of Computer Science at University of Illinois at Urbana-Champaign (UIUC) with Prof. Hanghang Tong.
I received my Ph.D. degree in Computer Science from Hanyang University under the supervision of Prof. Sang-Wook Kim.
Research Interest
- Network Science: Graph and Hypergraph Neural Networks, Dynamic Network Learning, Self-Supervised Learning on Networks
- Information Retrieval & Recommender Systems: Retrieval-Augmented Generation (RAG), Personalized Recommendation
- Applied Data Science: Time-Series Forecasting and Anomaly Detection, Knowledge Graph Embedding and Its Applications
- Trustworthy AI: Fairness, Diversity, and Explainability in Graph Learning, Machine Unlearning on Graphs
Publications (* indicates equal contributions)
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CROWN: A Novel Approach to Comprehending Users' Preferences for Accurate Personalized News Recommendation
Yunyong Ko, Seongeun Ryu, and Sang-Wook Kim
WWW 2025 | ACM Web Conference
Selected as an Oral Presentation of WWW 2025
Paper / Code
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HyGEN: Regularizing Negative Hyperedge Generation for Accurate Hyperedge Prediction
Song Kyung Yu, Da Eun Lee, Yunyong Ko, and Sang-Wook Kim
WWW 2025 (Short Paper) | ACM Web Conference
Paper / Code
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Enhancing Hyperedge Prediction with Context-Aware Self-Supervised Learning
Yunyong Ko, Hanghang Tong, and Sang-Wook Kim
TKDE | IEEE Transactions on Knowledge and Data Engineering (SCIE, 2025)
Paper / Code -
HearHere: Mitigating Echo Chambers in News Consumption through an AI-based Web System
Youngseung Jeon, Jaehoon Kim, Sohyun Park, Yunyong Ko, Seongeun Ryu, Sang-Wook Kim, and Kyungsik Han
CSCW 2024 | ACM Conference on Computer-Supported Cooperative Work and Social Computing
Paper -
SAGE: A Storage-Based Approach for Scalable and Efficient Sparse Generalized Matrix-Matrix Multiplication
{Myung-Hwan Jang*, Yunyong Ko*}, Hyuck-Moo Gwon, Ikhyeon Jo, Yongjun Park, and Sang-Wook Kim
CIKM 2023 | ACM International Conference on Information and Knowledge Management
Paper -
KHAN: Knowledge-Aware Hierarchical Attention Networks for Accurate Political Stance Prediction
Yunyong Ko, Seongeun Ryu, Soeun Han, Youngseung Jeon, Jaehoon Kim, Sohyun Park, Kyungsik Han, Hanghang Tong, and Sang-Wook Kim
WWW 2023 | ACM Web Conference
Paper / Code -
RealGraphGPU: A High-Performance GPU-Based Graph Engine toward Large-Scale Real-World Network Analysis
Myung-Hwan Jang, Yunyong Ko, Dongkyu Jeong, Jeong-Min Park, and Sang-Wook Kim
CIKM 2022 (Short Paper) | ACM International Conference on Information and Knowledge Management
Paper -
Not All Layers Are Equal: A Layer-Wise Adaptive Approach Toward Large-Scale DNN Training
Yunyong Ko, Dongwon Lee, and Sang-Wook Kim
WWW 2022 | ACM Web Conference
Paper / Code -
D-FEND: A Diffusion-Based Fake News Detection Framework for News Articles Related to COVID-19
Soeun Han, Yunyong Ko, Yusim Kim, Heejin Park, Seongsu Oh, and Sang-Wook Kim
SAC 2022 | ACM Symposium on Applied Computing
Paper -
MASCOT: A Quantization Framework for Efficient Matrix Factorization in Recommender Systems
{Yunyong Ko*, Jae-Su Yu*}, Hong-Kyun Bae, Yongjun Park, Dongwon Lee, and Sang-Wook Kim
ICDM 2021 | IEEE International Conference on Data Mining
Selected as One of the Best-ranked Papers of ICDM 2021 for fast-track journal invitation
Paper / Code -
ALADDIN: Asymmetric Centralized Training for Distributed Deep Learning
Yunyong Ko, Kibong Choi, Hyunseung Jei, Dongwon Lee, and Sang-Wook Kim
CIKM 2021| ACM International Conference on Information and Knowledge Management
Selected as a Spotlight Presentation of CIKM 2021
Paper / Appendix -
An In-Depth Analysis on Distributed Training of Deep Neural Networks
Yunyong Ko, Kibong Choi, Jiwon Seo, and Sang-Wook Kim
IPDPS 2021 | IEEE International Parallel and Distributed Processing Symposium
Paper
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Influence Maximization for Effective Advertisement in Social Networks: Problem, Solution, and Evaluation
Suk-Jin Hong, Yunyong Ko, Moon-Jeung Joe, and Sang-Wook Kim
SAC 2019 | ACM Symposium on Applied Computing
Paper -
Efficient and Effective Influence Maximization in Social Networks: A Hybrid-Approach
Yunyong Ko, Kyung-Jae Cho, and Sang-Wook Kim
Information Sciences (SCIE, 2018)
Paper
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Influence Maximization in Social Networks: A Target-Oriented Estimation
Yunyong Ko, Dong-Kyu Chae, and Sang-Wook Kim
Journal of Information Science (SCIE, 2018)
Paper
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Accurate Path-Based Influence Maximization in Social Networks
Yunyong Ko, Dong-Kyu Chae, and Sang-Wook Kim
WWW 2016 (Short Paper) | ACM Web Conference
Paper
Experiences
- University of Illinois at Urbana-Champaign (UIUC), Urbana, IL, USA • May 2022 - Feb. 2024
Postdoctoral Researcher, Department of Computer Science (Advisor: Prof. Hanghang Tong)
Topic: Large-Scale Hypergraph Learning for Real-World Applications - Hanyang University, Seoul, Korea • Sep. 2021 - Apr. 2022
Postdoctoral Researcher, Department of Computer Science (Advisor: Prof. Sang-Wook Kim)
Topic: Optimization Technique for Large-Batch DNN Training
- The Pennsylvania State University (PSU), University Park, PA, USA • Oct. 2019 - Feb. 2020
Visiting Scholar, College of Information Sciences and Technology (IST) (Advisor: Prof. Dongwon Lee)
Topic: Data Parallelism Approach for Distributed Deep Learning
Education
- Hanyang University, Seoul, Korea • Aug. 2021
Ph.D in Computer Science (Advisor: Prof. Sang-Wook Kim)
Thesis: Effective Approaches to Distributed Deep Learning: Methods, Analyses, and Evaluation
- Hanyang University, Seoul, Korea • Aug. 2013
B.S in Computer Science
Honors & Awards
- Scholarship and Teaching for Engineering Postdocs (STEP)
Grainger College of Engineering (GCOE), University of Illinois at Urbana-Champaign• 2023 - Best Ranked Papers of IEEE ICDM
IEEE International Conference on Data Mining• 2021 - Spotlight Presentations of ACM CIKM
ACM International Conference on Information and Knowledge Management• 2021 - Outstanding Ph.D. Dissertation Award
Research Institute of Industrial Science, Hanyang University • 2021 - ACM SIGAPP Student Travel Award
ACM Symposium on Applied Computing • 2019 - Naver Ph.D. Fellowship
Naver Corporation • 2017
Teaching
- Graduate School
CAU Data Mining (48768)• 2025 Spring - Undergraduate School
CAU Capstone Design (56120)• 2025 Spring
CAU Artificial Intelligence (17182)• Fall 2024
CAU Algorithm (13601)• Spring 2024-2025
CAU Database Design (34692)• Fall 2024
CAU Data Structure (40989)• Spring 2024
Professional Services
- Track Co-Chair
ACM Symposium on Applied Computing (SAC)• 2023 - 2025 - Program Committee Member (or Conference Reviewer)
ACM International Conference on Information and Knowledge Management (CIKM)• 2025
ACM Web Conference (WWW) • 2023 - 2025
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) • 2021, 2022, 2024, 2025
IEEE International Conference on Data Mining (ICDM) • 2022, 2023
AAAI International Conference on Artificial Intelligence (AAAI) • 2021
ACM Symposium on Applied Computing (SAC) • 2022, 2023
- Journal Reviewer
ACM Transactions on Knowledge Discovery from Data (TKDD) • 2025
ACM Computing Surverys (CSUR) • 2024
IEEE Transactions on Neural Networks and Learning Systems (TNNLS) • 2023, 2025
IEEE Transactions on Network Science and Engineering (TNSE) • 2024
Journal of Supercomputing • 2023