Yuanfeng Ji
Researcher specializing in artificial intelligence applications in medicine, focused on advancing reliable and impactful healthcare technologies.
About
I am dedicated to pioneering AI solutions in medical imaging and digital pathology. My work is driven by a commitment to developing robust and trustworthy systems that can contribute to advancements in healthcare diagnostics and treatment planning.
News
Hiring Internship Positions for Medical AGI Research
Our team is looking for talented interns to join us in exploring Medical AGI. For detailed information, please see the link. If you're interested and passionate, feel free to reach out directly!
Joined LiLab as a Postdoctoral Researcher
I completed my Ph.D. in August 2024 and have joined Li Lab at Stanford University as a postdoctoral researcher.
Work Experience
Stanford University
Postdoctoral Researcher
Engaged in AI applications for precision medicine under the guidance of Prof. Ruijiang Li.
Stanford University
Visiting Student Researcher
Engaged in AI applications for precision medicine under the guidance of Prof. Ruijiang Li.
Huawei Noah's Ark Lab
Research Intern
Developed AI models for predicting cancer treatment outcomes, focusing on precision medicine.
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.
Education
Shenzhen University
Bachelor's Degree in Electronic Information Engineering
City University of Hong Kong
Master's Degree in Electronic Information Engineering
The University of Hong Kong
MPhil in Computer Science
The University of Hong Kong
Ph.D. in Computer Science
Projects
DDP: Diffusion Model for Dense Visual Prediction
Developed a framework for dense visual predictions based on the conditional diffusion pipeline, following a 'noise-to-map' generative paradigm.
AMOS: A Large-Scale Abdominal Multi-Organ Benchmark
Created a comprehensive benchmark for abdominal multi-organ segmentation, facilitating advancements in medical image analysis.
DrugOOD: Out-of-Distribution Dataset Curator and Benchmark
Developed a dataset curator and benchmark for AI-aided drug discovery, focusing on affinity prediction problems with noisy annotations.
Publications
SlideChat: A Large Vision-Language Assistant for Whole-Slide Pathology Image UnderstandingTech Report
Ying Chen*, Guoan Wang*, Yuanfeng Ji*#, Yanjun Li, Jin Ye, Tianbin Li, Bin Zhang, Nana Pei, Rongshan Yu, Yu Qiao, Junjun He#
Yuanfeng Ji, Hao Chen, Dan Lin, Xiaohua Wu, Di Lin
Di Lin, Yuanfeng Ji, Dani Lischinski, Daniel Cohen-Or, Hui Huang
Awards & Achievements
Ranked 5th (Gold Medal)
Ranked 3rd
Ranked 87th (Silver Medal)