Sundong Kim PhD student at KAIST

Sundong Kim (김선동, 金先东)

Ph.D. Candidate, KAIST ISysE / KSE
E-mail: (at)
'Open-Minded', 'Opinionative', 'Optimist', 'Optimizer'

Here is my Curriculum Vitae. [PDF]
Here is my Work Portfolio. [Slides]

About Me

I recently completed my Ph.D. in Industrial & Systems Engineering at Korea Advanced Institute of Science and Technology (KAIST), advised by Jae-Gil Lee. My thesis research focused on predictive analytics using in-store sensor data. Last year, I interned with Microsoft Research Asia on user embedding using behavior data.

Quite a long time during my graduate studies, I was a TA in Viterbi iPodia program to help manage a course between several universities. Plus, I contributed fine-grained entity typing for Exobrain project as a RA. For master’s thesis, I worked on friend recommendation to reduce asymmetric relation.

During college year, I spent beautiful semesters in National University of Singapore, TU-Berlin, and in Deloitte.

I am always trying to be active in communication and find synergies between members, and I would like to pursue my career in that direction.

Selected Publications

  • A Systematic Framework of Predicting Customer Revisit with In-Store Sensors
    Sundong Kim, Jae-Gil Lee
    Knowledge and Information Systems. (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.

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