About Me
I am an Assistant Professor in the School of Computer Science and Engineering at Chung-Ang University (CAU).
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.
My research interests mainly lie in data mining and machine learning on various types of data (e.g., graph, hypergraph, text, and image), with a special focus on exploring knowledge for real-world applications.
At CAU, I lead the Data Mining and Intelligence Systems (DMIS) lab . Feel free to reach out to me if you are interested in joining our lab.
Positions
- Chung-Ang University (CAU), Seoul, Korea • Mar. 2024 - Present
- Assistant Professor, School of Computer Science and Engineering
- University of Illinois at Urbana-Champaign (UIUC), Urbana, IL, USA • May 2022 - Feb. 2024
- Postdoctoral Researcher, Department of Computer Science (Advisor: Prof. Hanghang Tong)
- Hanyang University, Seoul, Korea • Sep. 2021 - Apr. 2022
- Postdoctoral Researcher, Department of Computer Science (Advisor: Prof. Sang-Wook Kim)
- 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)
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
Publications (* indicates equal contributions)
Preprints
- CROWN: A Novel Approach to Comprehending Users' Preferences for Accurate Personalized News Recommendation
Yunyong Ko, Seongeun Ryu, and Sang-Wook Kim
arXiv:2310.09401 • [ Paper | Code ]
- Enhancing Hyperedge Prediction with Context-Aware Self-Supervised Learning
Yunyong Ko, Hanghang Tong, and Sang-Wook Kim
arXiv:2309.05798 • [ 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
ACM CSCW 2024 • [ Paper | Slides ]
- 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
ACM CIKM 2023 • [ Paper | Slides ] - 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 • [ Paper | Code | Slides ]
- 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
ACM CIKM 2022 (Short Paper) • [ Paper | Poster ] - 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 • [ Paper | Code | Slides ] - 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
ACM SAC 2022 • [ Paper ] - SHAT: A Novel Asynchronous Training Algorithm That Provides Fast Model Convergence in Distributed Deep Learning
Yunyong Ko and Sang-Wook Kim
Applied Sciences (SCIE, 2022) • [ 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
IEEE ICDM 2021 • [ Paper | Code | Slides ]
Selected as one of the best-ranked papers of ICDM 2021 for fast-track journal invitation - ALADDIN: Asymmetric Centralized Training for Distributed Deep Learning
Yunyong Ko, Kibong Choi, Hyunseung Jei, Dongwon Lee, and Sang-Wook Kim
ACM CIKM 2021 • [ Paper | Poster | Slides | Appendix ]
Selected as one of the spotlight presentations of CIKM 2021 - An In-Depth Analysis on Distributed Training of Deep Neural Networks
Yunyong Ko, Kibong Choi, Jiwon Seo, and Sang-Wook Kim
IEEE IPDPS 2021 • [ Paper | Slides ]
- Influence Maximization for Effective Advertisement in Social Networks: Problem, Solution, and Evaluation
Suk-Jin Hong, Yunyong Ko, Moon-Jeung Joe, and Sang-Wook Kim
ACM SAC 2019 • [ 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 ]
- 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 ]
- Accurate Path-Based Influence Maximization in Social Networks
Yunyong Ko, Dong-Kyu Chae, and Sang-Wook Kim
WWW 2016 (Short Paper) • [ Paper ]
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
Professional Services
- Track Co-Chair
ACM Symposium on Applied Computing (ACM SAC)• 2023 - Conference Reviewer
The ACM Web Conference (WWW) • 2023
The ACM SIGKDD Conference on Knowledge Discovery and Data Mining (ACM KDD) • 2021, 2022, 2024
The IEEE International Conference on Data Mining (IEEE ICDM) • 2022, 2023
The IEEE International Conference on Big Data (IEEE BigData), GTA3 Workshop • 2023
The AAAI International Conference on Artificial Intelligence (AAAI) • 2021
The ACM Symposium on Applied Computing (ACM SAC) • 2022, 2023
- Journal Reviewer
The IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS) • 2023
Journal of Supercomputing • 2023