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.

Publication

(conference, journal, and * denotes equal contribution)

• Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach
  Changdae Oh, Zhen Fang, Shawn Im, Xuefeng Du, Yixuan Li
  [paper]
  ICLR 2025 Workshop: Quantify Uncertainty and Hallucination in Foundation Models

• DaWin: Training-free Dynamic Weight Interpolation for Robust Adaptation
  [paper][code]
  Changdae Oh, Yixuan Li, Kyungwoo Song, Sangdoo Yun, Dongyoon Han
  ICLR 2025
  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
  NeurIPS 2023, Workshop on Distribution Shifts

• 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

• 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
  Changdae Oh, Gyeongdeok Seo, Geunyoung Jung, Zhi-Qi Cheng, Hosik Choi, Jiyoung Jung, Kyungwoo Song
  [paper]
  2024

• Enhancing Temporal Action Localization: Advanced S6 Modeling with Recurrent Mechanism
  Sangyoun Lee, Juho Jung, Changdae Oh, Sunghee Yun
  [paper]
  2024

• Graph Perceiver IO: A General Architecture for Graph Structured Data
  Seyun Bae, Hoyoon Byun, Changdae Oh, Yoon-Sik Cho, Kyungwoo Song
  [paper]
  2022

Education

• Ph.D. in Computer Science, University of Wisconsin-Madison
  advisor: Prof. Sharon Yixuan Li
  Sep. 2024 ~ Present

• M.S. in Artificial Intelligence, University of Seoul
  advisor: Prof. Kyungwoo Song and Prof. Jiyoung Jung
  Mar. 2022 - Aug. 2024

• B.S. in Statistics, University of Seoul
  Mar. 2016 - Feb. 2022

Experience

• Research Intern, NAVER AI Lab
  Mentor: Dongyoon Han and Sangdoo Yun, Apr. 2023 ~ Aug. 2024
  • DaWin: Training-free Dynamic Weight Interpolation for Robust Adaptation, ICLR 2025
• Visiting Scholar / Research Collaboration, Carnegie Mellon University
  Mentor: Zhi-Qi Cheng, Sep. 2023 ~ Feb. 2024
  
  • Towards Calibrated Robust Fine-Tuning of Vision-Language Model, NeurIPS 2024
  • Mitigating the Linguistic Gap with Phonemic Representations for Robust Cross-lingual Transfer, EMNLP 2024 Workshop

Academic Services

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