Sundong Kim (김선동, 金先东)

Research Fellow, IBS, Republic of Korea
E-mail: sundong (at) ibs.re.kr

[C.V.] [LinkedIn]

About Me

I am a research fellow in the Data Science Group at Institute for Basic Science, working with Meeyoung Cha. My research interests include predictive analytics by modeling effective features and architectures. Currently, I am working on customs fraud detection in collaboration with the World Customs Organization. I obtained my Ph.D. in Knowledge Service Engineering at Korea Advanced Institute of Science and Technology (KAIST), advised by Jae-Gil Lee. My thesis research focused on customer revisit prediction using in-store sensor data.


Internships

If you are interested in predictive analytics projects using point-of-interest dataset, please contact me.


Selected Publications

  • Deep Survival Analysis for Revisit Prediction
    Sundong Kim, Hwanjun Song, Sejin Kim, Beomyoung Kim, Jae-Gil Lee
    The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2020, Singapore. (Full Paper - Acceptance Rate: 21%)
    [Link] [PDF]

  • A Systematic Framework of Predicting Customer Revisit with In-Store Sensors
    Sundong Kim, Jae-Gil Lee
    Knowledge and Information Systems, 2019. (Invited Paper)
    [Link] [PDF]

  • Utilizing In-Store Sensors for Revisit Prediction
    Sundong Kim, Jae-Gil Lee
    The IEEE International Conference on Data Mining (ICDM) 2018, Singapore. (Full Paper - Acceptance Rate: 8.86%)
    (Selected as one of the best papers in ICDM 2018)
    [Link] [PDF] [Slides] [Poster] [Video] [Github]

  • Friend Recommendation with a Target User in Social Networking Services
    Sundong Kim
    The IEEE International Conference on Data Engineering (ICDEW) 2015, Seoul, Korea. (Ph.D. Symposium)
    [Link] [PDF] [Slides]

For the full list, please check my publication page, or check my C.V. including the list of working papers.


Recent News


Contact Details

  • E-mail: sundong (at) ibs.re.kr
  • WWW: http://seondong.github.io
  • Office: B233 (Theory), Institute of Basic Science, 55 Expo-ro, Yuseong-gu, Daejeon, Republic of Korea