Professor

About

  • I am an assistant professor in the Department of Industrial Engineering and Systems and also affiliated with the Graduate School of AI at KAIST.
  • Before joining KAIST, I was a postdoctoral research fellow in Computer Science at University of Illinois at Urbana-Champaign. I obtained my Ph.D degree in Computer Science and Engineering from Pohang University of Science and Technology (POSTECH), and B.S. in Computer Science from Sogang University.

Research Interest

  • Data-Centric AI, Model-Centric AI, Multimodal Data Mining, AI for Science
    • Mining meaningful knowledge from multimodal data to develop artificial intelligence solutions for various real-world applications across different disciplines.
    • Application domains: Recommendation system, AI for Science (Materials science, Chemistry, Bioinformatics), Large Language Model applications, Scene understanding, Social network analysis, Medical image analysis, Fraud/Anomaly detection, Knowledge graph, Sentiment analysis, Purchase/Click prediction, Time-series and spatio-temporal anlaysis, etc.

Announcements

  • I am actively seeking for passionate and self-motivated Ph.D. students, MS students, and postdocs. If you are interested, send me an email with your interests, CV, and transcript.
  • I am also looking for undergraduate students who are interested in doing internship in our lab, which will be open every summer and winter. If you are interested, send me an email with your interests, CV, and transcript.
    • Interns will get opportunities to study about research topics that our lab is focusing on, and participate in research projects with graduate students.
    • If you are interested in joining our lab as a graduate student, I strongly recommend you to do an internship before you apply.
  • There are three ways to join our lab. You can apply through 1) Department of Industrial Engineering and Systems or 2) Graduate School of Data Science or 3) Graduate School of AI.

Work Experience

  • KAIST (Korea Advanced Institute of Science and Technology), Daejeon, South Korea
    • Assistant Professor (2020.11 - Present)
  • University of Illinois at Urbana-Champaign, IL, USA
    • Postdoctoral Research Fellow in Computer Science Department (2019.3 - 2020.10)
    • Host: Prof. Jiawei Han
  • Microsoft Research, Beijing, China
  • NAVER, Seongnam, South Korea

Education

  • POSTECH (Pohang University of Science and Technology)
    • Ph.D. in Computer Science and Engineering (2019)
    • Dissertation: Recommendation Framework via Matrix Factorization and Translation
    • Advisor: Prof. Hwanjo Yu
  • Sogang University
    • B.S. in Computer Science and Engineering (2014)
    • Graduated with Honors (Magma Cum Laude)

Teaching

  • KSE801: Recommender System and Machine Learning on Graphs
    • Fall 2021, Fall 2022, Fall 2023
  • CoE202: Basics of Artificial Intelligence
    • Fall 2021
  • IE343: Statistical Machine Learning
    • Spring 2021, 2022, 2023, 2024
  • DS503: Machine Learning for Data Science
    • Spring 2023, 2024
  • KSE527: Deep Learning
    • Spring 2022

Awards

  • Gold Prize, 30th Samsung Humantech Paper Award (2024)
  • Technology Innovation Awards of College of Engineering, KAIST (2023)
  • Top Reviewer of NeurIPS 2023
  • Best Paper Award, ICML 2023 Workshop on Computational Biology (2023)
  • KAIST Excellence in Teaching Award of Year 2022, KAIST (2023)
  • Best Teaching Award, ISysE KAIST (2022)
  • ICDM 2018 Travel Award (2018)
  • Award of excellence, Microsoft Research Asia Internship Program, Beijing, China (2017)
  • Naver Ph.D Fellowship (2016)
  • Top 1.1% in RecSys Challenge (2015)

Talks

Academic Services

Conference Program Committee/Reviewer

  • ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) [2022-present]
  • The Web Conference (WWW) [2020-present]
  • AAAI Conference on Artificial Intelligence (AAAI), [2021-present]
  • Conference on Neural Information Processing Systemss (NeurIPS) [2022-present]
  • International Conference on Machine Learning (ICML) [2023-present]
  • The International Conference on Learning Representations (ICLR), 2022
  • ACM International Conference on Research and Development in Information Retrieval (SIGIR) [2023-present]
  • ACM International Web Search and Data Mining Conference (WSDM) [2023-present]
  • International Joint Conference on Artificial Intelligence (IJCAI) [2023-present]
  • ACM International Conference on Information and Knowledge Management (CIKM) [2023-present]
  • International ACM SIGIR Conference on Information Retrieval in the Asia Pacific (SIGIR-AP) [2023-present]
  • Learning on Graphs Conference (LoG) [2022-present]
  • The Web Conference (WWW) Poster Track, 2020
  • ACM International Conference on Information and Knowledge Management (CIKM) Short Paper Track, 2020
  • IEEE International Conference on Big Data (BigData) [2020-2023]
  • ECML-PKDD Research Track [2023-present]
  • ECML-PKDD Applied Data Science Track and Demo Track [2020-2021]
  • International Conference on Database Systems for Advanced Applications (DASFAA), 2021
  • International Conference on Big Data and Smart Computing (BigComp) 2023
  • International Conference on Internet and Web Applications and Services (ICIW) [2017-2018]
  • Graph Learning @ TheWebConf, 2022
  • International Joint Conference on Artificial Intelligence (IJCAI) - Special Track on AI for Good, 2022

Event Organizations

  • Proceedings Chair, The ACM International Conference on Information and Knowledge Management (CIKM) [2023]