Sundong Kim (김선동)

About Me

I am an assistant professor at GIST AI Graduate School. I lead Data Science Lab. In these days, I am interested in understanding and building a human-like AI with abstraction and reasoning.

Before joining GIST, I worked as a Young Scientist Fellow at Data Science Group, Institute for Basic Science (IBS). I worked on representation learning, predictive analytics, and democratizing AI for social goods (e.g., World Customs Organization).

From 2015 to 2019, I was a Ph.D. student at Data Mining Lab, KAIST. My thesis was about predicting offline customer behavior. I received my undergraduate and master degree from Dept. of Industrial and Systems Engineering at KAIST.

See this page and Fill this form if you are incoming MS/PhD students at GIST AI, or interested in joining our group as an undergraduate intern.

Office: AI Graduate School (S7) Room 204, GIST
E-mail: sundong (at) gist.ac.kr
Call: (+82)-62-715-6387

[CV] [Google Scholar]

Mini-ARC


Selected Publications (Full list)

ARC

Fraud Detection

  • Customs Import Declaration Datasets
    Chaeyoon Jeong, Sundong Kim, Jaewoo Park, Yeonsoo Choi
    Hands on Workshop at 17th Annual WCO PICARD Conference, 2022
    [Link] [Github] [Slides] [Photo]

  • Knowledge Sharing via Domain Adaptation in Customs Fraud Detection
    Sungwon Park, Sundong Kim, Meeyoung Cha
    AAAI 2022
    [Link]

  • Customs Fraud Detection in the Presence of Concept Drift
    Tung-Duong Mai, Kien Hoang, Aitolkyn Baigutanova, Gaukhartas Alina, Sundong Kim
    ICDMW 2021 (IncrLearn Workshop)
    [Link] [Video]

  • Active Learning for Human-in-the-loop Customs Inspection
    Sundong Kim, Tung-Duong Mai, Sungwon Han, Sungwon Park, Thi Nguyen Duc Khanh, Jaechan So, Karandeep Singh, Meeyoung Cha
    IEEE Transactions on Data and Knowledge Engineering, 2022. (SCI, IF=6.977)
    [Link] [Github]

  • DATE: Dual Attentive Tree-aware Embedding for Customs Fraud Detection
    Sundong Kim*, Yu-Che Tsai*, Karandeep Singh, Yeonsoo Choi, Etim Ibok, Cheng-Te Li, Meeyoung Cha
    KDD 2020 (Applied Data Science)
    [Link] [PDF] [Slides] [Talk] [Github] [Project] [Promotional video] [WCO News] [Press]

User Modeling

  • Revisit Prediction by Deep Survival Analysis
    Sundong Kim, Hwanjun Song, Sejin Kim, Beomyoung Kim, Jae-Gil Lee
    PAKDD 2020
    [Link] [PDF] [Slides] [Talk] [Github]

  • Utilizing In-Store Sensors for Revisit Prediction
    Sundong Kim, Jae-Gil Lee
    ICDM 2018
    (Selected as one of the best papers in ICDM 2018)
    (Longer version: Knowledge and Information Systems 2020 [Link])
    [Link] [PDF] [Slides] [Poster] [Talk] [Github]

  • Friend Recommendation with a Target User in Social Networking Services
    Sundong Kim
    ICDEW 2015 (Ph.D. Symposium)
    [Link] [PDF] [Slides]

Embedding Learning

  • FedX: Unsupervised Federated Learning with Cross Knowledge Distillation
    Sungwon Han, Sungwon Park, Fangzhao Wu, Sundong Kim, Chuhan Wu, Xing Xie, Meeyoung Cha
    ECCV 2022
    [PDF] [Github] [Poster] [Video]

  • Embedding Heterogeneous Hierarchical Structure
    Sundong Kim
    IC2S2 2021 (Extended Abstract)
    [PDF] [Github]

  • Improving Unsupervised Image Clustering With Robust Learning
    Sungwon Park*, Sungwon Han*, Sundong Kim, Danu Kim, Sungkyu Park, Seunghoon Hong, Meeyoung Cha
    CVPR 2021
    [Link] [Github]

  • Mitigating Embedding and Class Assignment Mismatch in Unsupervised Image Classification
    Sungwon Han, Sungwon Park, Sungkyu Park, Sundong Kim, Meeyoung Cha
    ECCV 2020
    [PDF] [Supplementary] [Github] [Talk] [Summary]

  • Neural User Embedding From Browsing Events
    Mingxiao An, Sundong Kim
    ECML-PKDD 2020 (Applied Data Science)
    [PDF] [Talk]

XAI & Data Science

  • Explainable Product Classification for Customs
    Eunji Lee, Sundong Kim, Sihyun Kim, Sungwon Park, Meeyoung Cha, Soyeon Jung, Suyoung Yang, Yeonsoo Choi, Sungdae Ji, Minsoo Song, Heeja Kim
    Korean Artificial Intelligence Association, 2021
    [Link] [Demo]

  • Response to COVID-19 with Probabilistic Programming
    Assem Zhunis, Tung-Duong Mai, Sundong Kim
    Frontiers in Public Health, 2022.
    Short version: 7th International Conference on Computational Social Science (IC2S2) 2021. (Extended Abstract)
    [Link] [Abstract] [Github]

  • Disruption in the Chinese E-Commerce During COVID-19
    Yuan Yuan, Muzhi Guan, Zhilun Zhou, Sundong Kim, Meeyoung Cha, Depeng Jin, Yong Li
    Frontiers in Computer Science, 2021
    [Link]

Active Learning

  • Coherence-based Label Propagation over Time Series for Accelerated Active Learning
    Yooju Shin, Susik Yoon, Sundong Kim, Hwanjun Song, Jae-Gil Lee, Byung Suk Lee
    ICLR 2022
    [Link]

  • Carpe Diem, Seize the Samples Uncertain “at the Moment” for Adaptive Batch Selection
    Hwanjun Song, Minseok Kim, Sundong Kim, Jae-Gil Lee
    CIKM 2020
    [Link] [PDF] [Talk] [Github] [Press]

  • Ada-Boundary: Accelerating the DNN Training via Adaptive Boundary Batch Selection
    Hwanjun Song, Sundong Kim, Minseok Kim, Jae-Gil Lee
    Machine Learning, 2020
    [Link] [Slides] [Talk] [Github]


Academic Services


Talks and Videos

  • Research:
    • A Glimpse of the Happy ARC Day 🧩: [Video]
    • Developing artificial intelligence to support human intelligence: [PDF]
    • Dual attentive tree-aware embedding for customs fraud detection: [KACT Webinar] [English] [French]
    • Revisit prediction by deep survival analysis [Talk]
    • Utilizing in-store sensors for revisit prediction [Talk]
  • Others:
    • Why did I become a researcher? [Talk] [PDF]
    • What I have done so far, what I am interested in. [PDF]
    • Machine learning approach for customs fraud detection [PDF]
    • Tools and approaches for applied science in the era of big data [PDF]

Students

I have been fortunate to work with many gifted students:

Graduate Students at GIST AI:

  • Join us!

Undergraduate Students at GIST AI:

  • Join us!

Graduate Students at IBS/KAIST Data Science Group (DS Group):

Undergraduate Students at IBS/KAIST Data Science Group:

Graduate Students at KAIST Data Mining Group:

  • Yooju Shin (→ PhD Student at KAIST DM Lab), 2017, 2021-2022
  • Minseok Kim (→ Applied Scientist at Amazon Alexa AI), 2017, 2019-2020
  • Hwanjun Song (→ Research Scientist at Naver AI Lab), 2019-2022

Undergraduate Students at KAIST Data Mining Group: