Changdae Oh

Changdae Oh

Ph.D. student at Department of Computer Sciences, University of Wisconsin-Madison

About Me

I am a Ph.D. student in Department of Computer Sciences at the University of Wisconsin-Madison, advised by Prof. Sharon Yixuan Li. Before joining Sharon’s group, I obtained my MS degree in Artificial Intelligence at the University of Seoul under supervision of Prof. Kyungwoo Song and Prof. Jiyoung Jung. I had the privilege of working with Zhi-Qi Cheng, Alexander Hauptmann, and David Mortensen during visiting at Carnegie Mellon University, and internship at NAVER AI Lab allows me to be advised by Dongyoon Han and Sangdoo Yun.

I am broadly interested in machine learning fundamentals and AI safety & reliability. Recently, I have explored the intersection of robustness under distribution shift and efficient adaptation of large-scale foundation models.

📢 Actively seeking a 2025 summer research internship (in US or outside)!
💭 Interest & Expertise: robustness under distribution shifts, efficient adaptation of foundation models, reliability of multimodal large language models, model merging, and machine learning fundamentals – [CV link]
📩 Feel free to contact me if you find any alignment :)

Publication

(conference, journal, and * denotes equal contribution)

  • DaWin: Training-free Dynamic Weight Interpolation for Robust Adaptation
    [paper][code]
    Changdae Oh, Yixuan Li, Kyungwoo Song, Sangdoo Yun, Dongyoon Han
    NeurIPS 2024, Workshop on Adaptive Foundation Models

  • Towards Calibrated Robust Fine-Tuning of Vision-Language Models
    Changdae Oh*, Hyesu Lim*, Mijoo Kim, Dongyoon Han, Sangdoo Yun, Jaegul Choo, Alexander Hauptmann, Zhi-Qi Cheng, Kyungwoo Song
    [paper] [code]
    NeurIPS 2024

  • TC-BERT: Large-scale Language Model for Korean Technology Documents
    [paper] [code]
    Taero Kim*, Changdae Oh*, Hyeji Hwang*, Eunkyeong Lee, Yewon Kim, Yunjeong Choi, Sungjin Kim, Hosik Choi, Kyungwoo Song
    The Journal of Supercomputing 2024

  • Mitigating the Linguistic Gap with Phonemic Representations for Robust Cross-lingual Transfer
    [paper]
    Haeji Jung, Changdae Oh, Jooeon Kang, Jimin Sohn, Kyungwoo Song, Jinkyu Kim, David R. Mortensen
    EMNLP 2024, Multilingual Representation Learning Workshop

  • Perturb-and-Compare Approach for Detecting Out-of-Distribution Samples in Constrained Access Environments
    Hee-young Lee*, Hoyoon Byun*, Changdae Oh, JinYeong Bak, Kyungwoo Song
    [paper]
    ECAI 2024

  • First Step for Theoretical and Practical Foundations of Robust Visual Prompting
    Gyeongdeok Seo*, Changdae Oh*, Kyungwoo Song
    IJCAI 2024, The Trustworthy AI Workshop

  • Language Model-guided Student Performance Prediction with Multimodal Auxiliary Information
    Changdae Oh, Minhoi Park, Sungjun Lim, Kyungwoo Song
    [paper] [code]
    Expert Systems with Applications 2024

  • Bibimbap: Pre-trained Models Ensemble for Domain Generalization
    Jinho Kang, Taero Kim, Yewon Kim, Changdae Oh, Jiyoung Jung, Rakwoo Chang, Kyungwoo Song
    [paper] [code]
    Pattern Recognition 2024

  • Towards Calibrated Robust Fine-Tuning of Vision-Language Models
    Changdae Oh, Mijoo Kim, Hyesu Lim, Junhyeok Park, Euiseog Jeong, Zhi-Qi Cheng, Kyungwoo Song
    [paper]
    NeurIPS 2023, Workshop on Distribution Shifts

  • Geodesic Multi-Modal Mixup for Robust Fine-tuning
    Changdae Oh*, Junhyuk So*, YongTaek Lim, Hoyoon Byun, Minchul Shin, Jong-June Jeon, Kyungwoo Song
    [paper] [code]
    NeurIPS 2023

  • Robust Contrastive Learning with Dynamic Mixed Margin
    [paper] [code]
    Junhyuk So*, YongTaek Lim*, Yewon Kim*, Changdae Oh, Kyungwoo Song
    IEEE Access 2023

  • BlackVIP: Black-Box Visual Prompting for Robust Transfer Learning
    [paper] [code]
    Changdae Oh, Hyeji Hwang, Hee-young Lee, YongTaek Lim, Geunyoung Jung, Jiyoung Jung, Hosik Choi, Kyungwoo Song
    CVPR 2023

  • Learning Fair Representation via Distributional Contrastive Disentanglement
    [paper] [code]
    Changdae Oh, Heeji Won, Junhyuk So, Taero Kim, Yewon Kim, Hosik Choi, Kyungwoo Song
    KDD 2022

Preprints

  • Robust Adaptation of Foundation Models with Black-Box Visual Prompting
    [paper]
    Changdae Oh, Gyeongdeok Seo, Geunyoung Jung, Zhi-Qi Cheng, Hosik Choi, Jiyoung Jung, Kyungwoo Song

  • Enhancing Temporal Action Localization: Advanced S6 Modeling with Recurrent Mechanism
    [paper]
    Sangyoun Lee, Juho Jung, Changdae Oh, Sunghee Yun

  • Graph Perceiver IO: A General Architecture for Graph Structured Data
    [paper]
    Seyun Bae, Hoyoon Byun, Changdae Oh, Yoon-Sik Cho, Kyungwoo Song

Education

Experience

  • Research Intern, NAVER AI Lab
    Mentor: Dongyoon Han and Sangdoo Yun, Apr. 2023 ~ Aug. 2024
  • Visiting Student / Collaborator, Carnegie Mellon University
    Mentor: Zhi-Qi Cheng, Sep. 2023 ~ Feb. 2024

Academic Services

  • Conference Reviewer: ICLR’25, AAAI’25, NeurIPS’24, CVPR’24
  • Conference Volunteer: NeurIPS’24, KDD’22