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Bryan Wong

Ph.D. Candidate
KAIST
bryan.wong (at) kaist.ac.kr


About Me

I am currently a Ph.D. candidate in Data Science at KAIST, advised by Prof. Mun Yong Yi, and have been fortunate to collaborate with and be mentored by Dr. Huazhu Fu at A*STAR. Before beginning my Ph.D., I received my M.S. in Data Science from KAIST in 2023 and completed my B.S. in Computer Science at NTUST in 2021, graduating one year early.

My research focuses on the data-efficient adaptation of vision–language models (VLMs) to domain-specific tasks. I have developed a method that adapts foundation VLMs to complex visual domains such as gigapixel images. I am now investigating how multimodal LLMs (MLLMs) can be adapted for domain-specific visual understanding with minimal supervision and without costly fine-tuning.

Overall, my goal is to enable scalable, explainable, and generalizable VLM/MLLM-based visual intelligence in resource-constrained or safety-critical real-world settings.

News

International Conference Publications

  1. NeurIPS
    Few-Shot Learning from Gigapixel Images via Hierarchical Vision-Language Alignment and Modeling
    Bryan Wong*, Jongwoo Kim*, Huazhu Fu, and Mun Yong Yi
    The Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS), 2025.
    (Acceptance rate: 5,290 / 21,575 = 24.52%)
    PDF Code OpenReview, Poster, Slide & Video BibTex

  2. EMNLP
    Not All Options Are Created Equal: Textual Option Weighting for Token-Efficient LLM-Based Knowledge Tracing
    Jongwoo Kim*, SeongYeub Chu*, Bryan Wong, and Mun Yong Yi
    Conference on Empirical Methods in Natural Language Processing (EMNLP Findings), 2025.
    (Acceptance rate: 1,812 / 8,174 = 22.16% for Main; 1,420 / 8,174 = 17.35% for Findings)
    PDF Code Poster BibTex

  3. CIKM
    Leveraging Multi-facet Paths for Heterogeneous Graph Representation Learning
    Jongwoo Kim, SeongYeub Chu, Hyeongmin Park, Bryan Wong, Keejun Han, and Mun Yong Yi
    34th ACM International Conference on Information and Knowledge Management (CIKM), 2025.
    (Acceptance rate: 443 / 1,627 = 27%)
    PDF Code BibTex

  4. MICCAI
    MicroMIL: Graph-based Contextual Multiple Instance Learning for Patient Diagnosis Using Microscopy Images
    Jongwoo Kim*, Bryan Wong*, Huazhu Fu, Willmer Rafell Quiñones Robles, Young Sin Ko, and Mun Yong Yi
    28th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2025.
    (Acceptance rate: 1,014 / 3,447 = 29%)
    PDF Code Poster BibTex

  5. NAACL
    Rationale Behind Essay Scores: Enhancing S-LLM’s Multi-Trait Essay Scoring with Rationale Generated by LLMs
    SeongYeub Chu*, Jongwoo Kim*, Bryan Wong, and Mun Yong Yi
    Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL Findings), 2025.
    PDF Code Poster BibTex

  6. ISBI
    Rethinking Pre-Trained Feature Extractor Selection in Multiple Instance Learning for Whole Slide Image Classification
    Bryan Wong, Sungrae Hong, and Mun Yong Yi
    IEEE International Symposium on Biomedical Imaging (ISBI), 2025.
    PDF Code Poster BibTex

  7. ISBI
    Towards Classifying Histopathological Microscope Images as Time Series Data
    Sungrae Hong, Hyeongmin Park, Youngsin Ko, Sol Lee, Bryan Wong, and Mun Yong Yi
    IEEE International Symposium on Biomedical Imaging (ISBI), 2025.
    PDF Poster BibTex

  8. IC2S2 & KCC
    Analyzing Gender Pay Gap in STEM Fields by Life Trajectory
    Wenchao Dong, Bryan Wong, Hasnain Irshad Bhatti, Lanu Kim, and Meeyoung Cha
    8th International Conference on Computational Social Science (IC2S2) and Korea Computer Congress (KCC), 2022.
    PDF Poster BibTex

    9. International Journal Publications

    1. BMC
      A predicted-loss based active learning approach for robust cancer pathology image analysis in the workplace
      Mujin Kim, Willmer Rafell Quiñones Robles, Young Sin Ko, Bryan Wong, Sol Lee, and Mun Yong Yi
      BMC Medical Imaging, 2024.
      PDF BibTex

      2. Preprint

      1. Preprint, 2025.
        Leveraging Spatial Context for Positive Pair Sampling in Histopathology Image Representation Learning
        Willmer Rafell Quinones Robles, Sakonporn Noree, Young Sin Ko, Bryan Wong, Jongwoo Kim, and Mun Yong Yi
        Preprint, 2025.
        PDF Code BibTex

      2. Preprint
        PreMix: Label-Efficient Multiple Instance Learning via Non-Contrastive Pre-training and Feature Mixing
        Bryan Wong and Mun Yong Yi
        Preprint, 2024.
        PDF Code BibTex

        3. Academic Services

        • Reviewer: MICCAI 2025,
        • Student Volunteer: MICCAI 2025

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