Seoyoung Hong

Machine Learning Researcher 💻

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E-mail: seoyoung.hong@boeing.com
Phone: +82-10-7120-6128

I am currently employed as a Machine Learning Researcher at Boeing Korea. I completed my master’s degree at Big Data Analytics Lab, Yonsei University.

My research interests include recommender systems, predictive modeling, and time-series forecasting. I enjoy solving various real-world problems with data-driven deep learning algorithms. Here is a full Curriculum Vitae.

When I’m not looking at code, I can usually be found playing tennis, baking, or watching films. I desire to be someone who contributes to and changes the world. I want to live forever young, as my name says!


Experience

  • Machine Learning researcher at Boeing Korea
    Jan. 2024 - Present
    Boeing Korea (BKETC), Seoul, Korea

  • Visiting researcher in Computational Science & Engineering
    Jan. 2023 - Jun. 2023
    Georgia Institute of Technology, Atlanta, United States

  • Google Machine Learning Bootcamp
    Oct. 2020 - Jan. 2021
    Google Developers, Seoul, Korea


Education

  • Master’s degree in Artificial Intelligence
    Sep. 2021 - Aug. 2023
    Yonsei University, Seoul, Korea

  • Bachelor’s degree in Business
    Bachelor’s degree in Software (Data Science)
    Mar. 2016 - Feb. 2021
    Kyunghee University, Seoul, Korea

  • Exchange Student
    Jan. 2018 - Jun. 2018
    University of Leicester, Leicester, UK


Awards

  • Best Student Paper award at IEEE Bigdata 2022
    Dec. 2022
    “TimeKit: A Time-series Forecasting-based Upgrade Kit for Collaborative Filtering” has won the Best Student Paper award at IEEE BigData 2022.

  • KSC 2020 Junior Paper Awards, 4th Prize (학부생/주니어논문경진대회 장려상)
    Feb. 2021
    Hosted by the Korean Institute of Information Scientists and Engineers

  • Big Contest 2020, 2nd prize (2020 빅콘테스트 퓨처스리그 최우수상)
    Sep. 2020
    Hosted by the National Information Society Agency


News

Apr 23, 2023 A full research paper, titled “GREAD: Graph Neural Reaction-Diffusion Networks,” is accepted at ICML 2023!
Apr 5, 2023 A full research paper, titled “Blurring-Sharpening Process Models for Collaborative Filtering,” is accepted at SIGIR 2023!
Dec 19, 2022 My paper on “TimeKit: A Time-series Forecasting-based Upgrade Kit for Collaborative Filtering” has won the Best Student Paper award at IEEE BigData 2022!
Oct 25, 2022 A full research paper, titled “TimeKit: A Time-series Forecasting-based Upgrade Kit for Collaborative Filtering,” is accepted at IEEE BigData 2022.
Aug 1, 2022 A full research paper, titled “Prediction-based One-shot Dynamic Parking Pricing,” is accepted at CIKM 2022.

Publications

  1. GREAD: Graph Neural Reaction-Diffusion Networks
    Jeongwhan Choi, Seoyoung Hong, Noseong Park, and 1 more author
    In International Conference on Machine Learning (ICML) 2023
  2. Blurring-Sharpening Process Models for Collaborative Filtering
    Jeongwhan Choi, Seoyoung Hong, Noseong Park, and 1 more author
    In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval 2023
  3. TimeKit: A Time-series Forecasting-based Upgrade Kit for Collaborative Filtering
    Seoyoung Hong, Minju Jo, Seungji Kook, and 4 more authors
    In IEEE International Conference on Big Data (IEEE BigData) 2022
  4. Prediction-based One-shot Dynamic Parking Pricing
    Seoyoung Hong, Heejoo Shin, Jeongwhan Choi, and 1 more author
    In Proceedings of the 31st ACM International Conference on Information & Knowledge Management 2022
  5. Attentive neural controlled differential equations for time-series classification and forecasting
    Sheo Yon Jhin, Heejoo Shin, Seoyoung Hong, and 6 more authors
    In IEEE International Conference on Data Mining (ICDM) 2021
  6. Large-Scale Data-Driven Airline Market Influence Maximization
    Duanshun Li, Jing Liu, Jinsung Jeon, and 4 more authors
    In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining 2021