Yuanfeng Ji
AI researcher building foundation models for biomedicine.
Biomedical Foundation Models / Medical Computer Vision / AI Agents
About
I am a Staff Research Scientist at Ant Healthcare, developing frontier AI systems for healthcare. Previously, I was a postdoctoral scholar at Stanford University with Prof. Ruijiang Li, where I worked on AI foundation models for biomedicine, with a focus on computational pathology, radiology, and spatial biology. I received my PhD from HKU MMLab in 2024, advised by Prof. Ping Luo. My research spans generative models, vision-language models, and AI agents, translating frontier AI into clinically impactful tools for diagnosis, treatment, and biomedical discovery. See research scope →
“We have several full-time and internship openings at Ant Healthcare — email me.”
News
Joined Ant Healthcare as a Staff Research Scientist
I joined Ant Healthcare as a Staff Research Scientist, focusing on frontier AI research for healthcare.
SlideChat Published Online in Nature Cancer
SlideChat was published online in Nature Cancer. Congratulations to Ying Chen and Chenglong Ma!
nnMIL Published in Nature Biomedical Engineering
Published nnMIL, a generalizable multiple instance learning framework for computational pathology, in Nature Biomedical Engineering. Congratulations to Xiangde!
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Received a Biswas Family Foundation Fast Grant
Received USD 50,000 from the Biswas Family Foundation to lead the 2026–2027 project“An AI Co-Scientist for Spatial-Proteomics Biomarker Discovery.”
Cell Paper Published
Published a collaborative study in Cell on virtual spatial tumor profiling from histopathology.
Two Papers Accepted to ICML 2026
Two collaborative papers were accepted to ICML 2026.
ChexGen Accepted by NEJM AI
ChexGen, a generative foundation model for chest radiography, was accepted by NEJM AI.
GAIA Workshop Opened Its Call for Papers
The GAIA workshop at ICCV 2025 opened its call for papers on medical image generation, vision-language foundation models, and clinical workflow intelligence.
Two Papers Accepted to MICCAI 2025
Two collaborative papers were accepted to MICCAI 2025, including “Towards Interpretable Counterfactual Generation via Multimodal Autoregression” as an Early Accept.
GAIA Workshop Accepted to ICCV 2025
The GAIA workshop proposal was accepted to ICCV 2025 to bring together researchers in generative AI for biomedical image analysis.
Served as an Area Chair for MICCAI 2025
Served as an Area Chair for MICCAI 2025, contributing to the conference review process.
Two Papers Accepted to CVPR 2025
Two collaborative papers were accepted to CVPR 2025.
Joined Li Lab as a Postdoctoral Researcher
Joined Li Lab at Stanford University as a postdoctoral researcher after completing my PhD in August 2024.
Selected Publications
Full publication list →
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Yuanfeng Ji*, Chongjian Ge*, …, Ping Luo
Yuanfeng Ji, Ruimao Zhang, Zhen Li, Jiamin Ren, Shaoting Zhang, Ping Luo
Yuanfeng Ji, Hao Chen, Dan Lin, Xiaohua Wu, Di Lin
Education
The University of Hong Kong
Ph.D. in Computer Science
The University of Hong Kong
MPhil in Computer Science
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City University of Hong Kong
Master's Degree in Electronic Information Engineering
Shenzhen University
Bachelor's Degree in Electronic Information Engineering
Work Experience
Stanford University
Postdoctoral Researcher
Developing multimodal foundation models and AI agents for computational pathology, radiology, and spatial biology.
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Stanford University
Visiting Student Researcher
Developed generative and vision-language models for precision medicine, with a focus on chest radiography and whole-slide computational pathology.
Huawei Noah's Ark Lab
Research Intern
Developed vision foundation models for dense visual prediction tasks.
Tencent AI Lab
Research Intern
Led the development of a DrugAI dataset and benchmark for out-of-distribution generalization; developed multi-protein docking algorithms incorporating graph-based deep learning techniques.
SenseTime Research
Research Intern
Developed automated machine learning algorithms for medical image analysis; led the creation of a multi-site abdominal organ segmentation dataset and benchmark.
Imsight Medical Technology
Deep Learning Researcher
Led the development of CAD products implemented in several institutions in Hong Kong, including a chest X-ray diagnostic system detecting 17 lung diseases and a sequencing algorithm optimizing diagnostic queues at medical facilities.
Visual Computing Research Center, Shenzhen University
Research Assistant
Under the supervision of Prof. Hui Huang and Prof. Di Lin, contributed to research on semantic segmentation.