Curriculum vitae

Research interests

AI for biology, protein design, multi-omics, and virtual cells. My doctoral research includes foundation models for immunology, structure-based computational protein engineering, and AI agents for scientific discovery.

Education

Experience

Selected publications

Additional publications and abstracts are listed in the PDF CV.

1. Computational identification of antigen-specific T cell groups through generative epitope modeling

   M. Ma, W. Tu, C. Vasquez-Rios, J. Ding

   iScience, 2026

2. EpitopeGen: Learning to Generate T Cell Epitopes: A Semi-Supervised Approach with Biological Constraints

   M. Ma, W. Tu, C. Vasquez-Rios, J. Ding

   ICML Workshop on Generative AI and Biology (GenBio), 2025

3. Clinical validation of artificial intelligence-powered PD-L1 tumor proportion score interpretation for immune checkpoint inhibitor response prediction in non-small cell lung cancer

   H. Kim, S. Kim, S. Choi, C. Park, S. Park, S. Pereira, M. Ma, D. Yoo, K. Paeng, W. Jung, S. Park, C. Ock, S. Lee, Y. Choi, J. Chung

   JCO Precision Oncology, 2024

4. An artificial intelligence-powered PD-L1 combined positive score (CPS) analyser in urothelial carcinoma alleviating interobserver and intersite variability

   K. Lee, E. Choi, S. Cho, S. Park, J. Ryu, A. V. Puche, M. Ma, J. Park, W. Jung, J. Ro, S. Kim, G. Park, S. Song, C. Ock, G. Choe, J. Park

   Histopathology, 2024

5. Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes as a predictive biomarker for axitinib in adenoid cystic carcinoma

   D. Kim, Y. Lim, C. Ock, G. Park, S. Park, H. Song, M. Ma, M. Mostafavi, E. Kang, M. Ahn, K. Lee, J. Kwon, Y. Yang, Y. Choi, M. Kim, J. Ji, T. Yun, S. Kim, Bhumsuk

   Head & Neck, 2023

6. Deep learning model improves tumor-infiltrating lymphocyte evaluation and therapeutic response prediction in breast cancer

   S. Choi, S. Cho, W. Jung, T. Lee, S. Choi, S. Song, G. Park, S. Park, M. Ma, S. Pereira, D. Yoo, S. Shin, C. Ock, S. Kim

   npj Breast Cancer, 2023

7. Artificial Intelligence-Powered Spatial Analysis of Tumor-Infiltrating Lymphocytes as Complementary Biomarker for Immune Checkpoint Inhibition in Non-Small-Cell Lung Cancer

   S. Park, C. Ock, H. Kim, S. Pereira, S. Park, M. Ma, S. Choi, S. Kim, S. Shin, J. Aum, K. Paeng, D. Yoo, H. Cha, S. Park, K. Suh, H. Jung, S. Kim, Y. Kim, J. Sun, J. Chung, J. Ahn, M. Ahn, J. Lee, K. Park, S. Song, Y. Bang, Y. Choi, T. Mok, S. Lee

   Journal of Clinical Oncology, 2022

8. Artificial intelligence-powered programmed death ligand 1 analyzer reduces interobserver variation in tumour proportion score for non-small cell lung cancer with better prediction of immunotherapy response

   S. Choi, S. Cho, M. Ma, S. Park, S. Pereira, J. Aum, S. Shin, K. Paeng, D. Yoo, W. Jung, C. Ock, S. Lee, Y. Choi, J. Chung, T. Mok, H. Kim, S. Kim

   European Journal of Cancer, 2022

9. Diagnostic assessment of deep learning algorithms for frozen tissue section analysis in women with breast cancer

   Y. Kim, I. Song, S. Cho, S. Kim, M. Kim, S. Ahn, H. Lee, D. Yang, N. Kim, S. Kim, T. Kim, D. Kim, J. Choi, K. Lee, M. Ma, M. Jo, S. Park, G. Gong

   2022

10. VLANet: Video-Language Alignment Network for Weakly-Supervised Video Moment Retrieval

    M. Ma*, S. Yoon, J. Kim, Chang D. Yoo

    ECCV, 2020

11. Modality Shifting Attention Network for Multi-modal Video Question Answering

    J. Kim, M. Ma, T. Pham, K. Kim, Chang D. Yoo

    CVPR, 2020

12. Progressive Attention Memory Network for Movie Story Question Answering

    J. Kim, M. Ma, K. Kim, S. Kim, Chang D. Yoo

    CVPR, 2019

13. Gaining Extra Supervision via Multi-task learning for Multi-Modal Video Question Answering

    J. Kim*, Minuk Ma*, K. Kim, S. Kim, Chang D. Yoo

    IJCNN (oral presentation)

Awards and honors

Patent application

Method and system for training a machine learning model to detect abnormal regions in pathological slide images.

KR 10-2021-0120991 (application)