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. My research interests mainly lie in data mining and machine learning on various types of data (including but not limited to graph, hypergraph, text, image, and time-series) with a special focus on exploring knowledge for real-world applications.

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
  • Hanyang University, Seoul, Korea Sep. 2021 - Apr. 2022
  • 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 ]
2024 and Forthcoming
  • 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 ]
2023
  • 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 ]
2022
  • 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 | Slides ]
2021
  • 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 ]
~ 2020
  • 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 ACM Computing Surverys (ACM CSUR) 2024
    The IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS) 2023
    Journal of Supercomputing 2023