I am a Ph.D. student in Electrical Engineering at KAIST, advised by Prof. Changick Kim.

My research interests include representation learning, self-supervised vision models (e.g., DINO), world models, and high-resolution weather forecasting . I particularly enjoy short-term performance tuning challenges , where rapid iteration and optimization are critical.

I am a multi-time challenge winner , including:
๐Ÿฅ‡ CVPR 2022 BMTT Challenge โ€“ Winner
๐Ÿฅ‡ NeurIPS VisDA 2022 Challenge โ€“ Winner
๐Ÿฅ‡ NeurIPS Weather4Cast 2022 Challenge โ€“ Winner
๐Ÿฅ‡ ICCV GeoNet 2023 Challenge โ€“ Winner

Currently, I am not collaborating on any topics other than weather forecasting and test-time optimization.

Contact

  • msseok96 [at] gmail.com

    minseok.seo [at] kaist.ac.kr

  • 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea

Education

  • PhD in EE, KAIST, 2025~

    on "Vision Foundation Model (TODO)"

  • MS in EE, KAIST, 2023

    on "Domain Adaptation"

  • MS in EE, Hanbat National University, 2021

    on "Active Learning for AI application"

  • BS in EE, Hanbat National University, 2020

Academic Activities

  • Program Committee in AAAI2025
  • Reviewer at CVPR, NeurIPS, ICLR, ICCV, ECCV, ICML, AAAI, TNNLS, TIP

Research Experiences

  • ANTLAB, Daejeon, Korea
    Sep 2025 ~

    CTO, ANTLAB
  • SI-Analytics (military service) , Daejeon, Korea
    Mar 2022 - Sep 2025

    Research Scientist, SI-Analytics

Publications

    Vision Foundation Model

  • Visual Self-Supervised Learning in Practice: A Survey of Alignment-, Reconstruction-, and Prediction-Based Paradigms

    Minseok Seo, Inyong Koo, Young-tack Oh, Young-Jae Park, Dong-geol Choi, Hae-Gon Jeon, Changick Kim

    arXiv 2026

    [ paper / code ]

  • Upsample Anything: A Simple and Hard to Beat Baseline for Feature Upsampling

    Minseok Seo, Mark Hamilton, Changick Kim

    arXiv 2025

    [ paper / code ]

  • VideoTitans: Scalable Video Prediction with Integrated Short-and Long-term Memory

    Young-Jae Park*, Minseok Seo*, Hae-Gon Jeon

    NeurIPS 2025

    [ paper / code ]

    • Weather AI

  • Station2Radar: queryโ€‘conditioned gaussian splatting for precipitation field

    Doyi Kim, Minseok Seo, Changick Kim

    ICLR 2026 (ORAL)

    [ paper / code ]

  • Data-driven Precipitation Nowcasting Using Satellite Imagery

    Young-Jae Park, Doyi Kim, Minseok Seo, Hae-Gon Jeon, Yeji Choi

    AAAI 2025 (ORAL)

    [ paper / code ]

  • Probabilistic Weather Forecasting with Deterministic Guidance-based Diffusion Model

    Donggeun Yoon* , Minseok Seo , Doyi Kim, Yeji Choi, and Donghyeon Cho

    ECCV 2024

    [ paper / code ]

  • Long-Term Typhoon Trajectory Prediction: A Physics-Conditioned Approach Without Reanalysis Data

    Young-Jae Park*, Minseok Seo*, Doyi Kim, Hyeri Kim, Sanghoon Choi, Beomkyu Choi, Jeongwon Ryu, Sohee Son, Hae-Gon Jeon, Yeji Choi

    ICLR 2024 (Spotlight)

    [ paper / code ]

  • Masked Autoregressive Model for Weather Forecasting

    Doyi Kim*, Minseok Seo*, Hakjin Lee, Junghoon Seo

    arXiv 2024

    [ paper / code ]

  • Weather4cast at neurips 2022: Super-resolution rain movie prediction under spatio-temporal shifts

    Weather4Forecast (Winner)

    NeurIPS 2022 competition track

    [ paper / code ]

    • Application

  • Self-Pair: Synthesizing Changes From Single Source for Object Change Detection in Remote Sensing Imagery

    Minseok Seo, Hakjin Lee, Yongjin Jeon, Junghoon Seo

    WACV 2023

    [ paper / code ]

  • Bidirectional domain mixup for domain adaptive semantic segmentation

    Daehan Kim*, Minseok Seo*, Kwanyong Park, Inkyu Shin, Sanghyun Woo, In So Kweon, Dong-Geol Choi

    AAAI 2023 (ORAL)

    [ paper / code ]

  • VisDA 2022 challenge: Domain adaptation for industrial waste sorting

    VisDA (Winner)

    NeurIPS 2022 Competition Track

    [ paper / code ]

  • Unsupervised change detection based on image reconstruction loss

    Hyeoncheol Noh*, Jingi Ju*, Minseok Seo*, Jongchan Park, Dong-Geol Choi

    CVPR 2022

    [ paper / code ]

  • Pt4al: Using self-supervised pretext tasks for active learning

    John Seon Keun Yi*, Minseok Seo*, Jongchan Park, Dong-Geol Choi

    ECCV 2022

    [ paper / code ]

  • A self-supervised sampler for efficient action recognition: Real-world applications in surveillance systems

    Minseok Seo, Donghyeon Cho, Sangwoo Lee, Jongchan Park, Daehan Kim, Jaemin Lee, Jingi Ju, Hyeoncheol Noh, Dong-Geol Choi

    RAL-ICLR 2021

    [ paper / code ]

  • OCR-based Inventory Management Algorithms Robust to Damaged Images

    Minseok Seo, Daehan Kim, Hyeyoon Kang, Donghyeon Cho, Dong-Geol Choi

    ICRA 2021

    [ paper / code ]

Research Collaboration