Jeya Maria Jose

I am a Senior Researcher at Microsoft Research, training frontier multimodal foundation models for medicine and science. My work spans pretraining at scale, representation learning, and turning real-world biomedical data into scientific discovery and better patient care.

Previously, I was a postdoctoral researcher at Stanford University, working with Andrew Ng and Curtis Langlotz. I obtained my Ph.D. and M.S from Johns Hopkins University advised by Vishal M Patel .

I am glad to be recognized as an Amazon fellow . I also had the opportunity to work with research teams at Google, NVIDIA , and Adobe during my Ph.D.

Email  /  CV  /  Google Scholar  /  Github  /  LinkedIn

News

  • June, 2026 - Our work on Frontier Model Robustness in Health AI accepted at Nature Medicine!!
  • June, 2026 - Invited Talk at Yale University (BIDS Rising Star Seminar).
  • June, 2026 - Invited Talk at CVPR 2026 (Recent advances in medical imaging workshop).
  • March, 2026 - 1 paper accepted at CVPR 2026.
  • March, 2026 - Merlin accepted at Nature!!
  • December, 2025 - GigaTIME accepted at Cell!! Media coverage by CNBC , Geekwire, Oncodaily , etc.
  • September, 2025 - Speaking as a panelist in MLLMs in Clinical Practice Workshop at MICCAI 2025.
  • July, 2025 - 1 paper accepted at ICCV 2025.
  • June, 2025 - Organizing Multi-modal Models and Medicine Workshop at CVPR 2025.
  • January, 2025 - 1 paper accepted at ICLR 2025.
  • October, 2024 - Won the Young Scientist Impact Award from MICCAI Society.
  • August, 2024 - 1 paper accepted at WACV 2025.
  • July, 2024 - 1 paper accepted at ECCV 2024.
  • April, 2024 - 4 papers accepted at MIDL 2024.
  • February, 2024 - Serving as Area Chair for MICCAI 2024.
  • October, 2023 - 1 paper accepted at WACV 2024.
  • November, 2023 - Won the DAAD AI-Net Fellowship.
  • August, 2023 - Invited Talk at MedAI Group. Link for Slides, Video.
  • May, 2023 - Invited Talk at Amazon. Link for Slides.
  • April, 2023 - Defended my Ph.D.!! Link for Slides.
  • March, 2023 - 1 paper accepted at MIDL 2023.
  • February, 2023 - 1 paper accepted at CVPR 2023.
  • January, 2023 - 1 paper accepted at ICLR 2023.
  • October, 2022 - Won the Amazon Research Fellowship.
  • September, 2022 - Received Young Scientist Impact Award - Finalist at MICCAI 2022.
  • August, 2022 - 1 paper accepted at WACV 2023.
  • August, 2022 - Received NIH MICCAI Award 2022, which rewards early career scientists.
  • June, 2022 - 3 papers accepted at MICCAI 2022.
  • June, 2022 - Invited Talk at IEEE SPS Summer School on AI in Healthcare.
  • May, 2022 - Awarded Outstanding Automation Paper Finalist (top 3) at ICRA 2022.
  • March, 2022 - Presented a Tutorial at ISBI 2022 on medical image segmentation.
  • March, 2022 - 1 paper accepted at CVPR 2022.
  • January, 2022 - 1 paper accepted at ICRA 2022.
  • November, 2021 - 1 paper accepted in IEEE Transactions on Medical Imaging.
  • June, 2021 - 2 papers accepted at MICCAI 2021.
  • May, 2021 - Joined Adobe as a Research Intern.
  • May, 2021 - 1 paper accepted at ICIP 2021 .
  • November, 2020 - 1 paper accepted in IEEE Journal of Selected Topics in Signal Processing .
  • November, 2020 - 1 paper accepted at WACV 2021 .
  • July, 2020 - Recipient of MICCAI Student Travel Award 2020, which rewards first author students of the highest-quality MICCAI papers.
  • May, 2020 - 1 paper accepted in the IEEE Journal of Selected Topics in Signal Processing .
  • May, 2020 - 1 paper accepted at MICCAI 2020 (Early Acceptance).
    • September, 2019 - Awarded Best Student Paper award at CVIP 2019 .
  • August, 2019 - Joined Johns Hopkins University for my Ph.D with ECE fellowship.



Research

Actual H&E input and GigaTIME-Flash predicted virtual mIF: DAPI, CD34 and CD68 composite.

GigaPath-Flash and GigaTIME-Flash: Efficient Pathology Foundation Models for Whole-Slide and Tumor Microenvironment Analysis

Naoto Usuyama*, Jeya Maria Jose Valanarasu*, Sicong Yao*, Hanwen Xu*, Jaspreet Bagga, Guanghui Qin, Robert E. Kramer, Cliff Wong, Soohee Lee, Hao Qiu, Theodore Zhengde Zhao, Racheli Ben Shimol, Angela Crabtree, Kevin Matlock, Eduardo Alejandro Lozano Garcia, Naiteek Sangani, Alberto Santamaria-Pang, Jason Entenmann, Alexandra Q. Bartlett, Bill J. Wright, Bernard A. Fox, Brian Piening, Sheng Zhang, Sheng Wang, Tristan Naumann, Carlo Bifulco, Hoifung Poon

Tech Report

Paper GigaPath-Flash GigaTIME-Flash
Evaluating the robustness and readiness of large frontier models in health AI applications preview

Evaluating the robustness and readiness of large frontier models in health AI applications

Yu Gu, Jingjing Fu, Xiaodong Liu, Jeya Maria Jose, Noel C. F. Codella, Reuben Tan, Qianchu Liu, Ying Jin, Sheng Zhang, Jinyu Wang, Rui Wang, Lei Song, Guanghui Qin, Naoto Usuyama, Cliff Wong, Hao Cheng, HoHin Lee, Praneeth Sanapathi, Sarah Hilado, Tristan Naumann, Javier Alvarez-Valle, Jiang Bian, Mu Wei, Khalil Malik, Lidong Zhou, Jianfeng Gao, Eric Horvitz, Matthew P. Lungren, Doug Burger, Eric Topol, Hoifung Poon, Paul Vozila

Nature Medicine

Paper Code