Medical Foundation Models
Generative models and synthetic data for breast imaging, with applications in screening, diagnosis and prognosis.
Explore researchPhD Candidate · Peking University
Youcheng Li · 利友诚
Medical AI, generative models and diagnostic reasoning
I am a PhD candidate in Artificial Intelligence at the School of Intelligence Science and Technology, Peking University, advised by Prof. Liwei Wang.
My research connects medical image analysis, generative foundation models and diagnostic reasoning. I develop models and benchmarks for breast ultrasound and mammography, and have worked on cell segmentation for spatial transcriptomics. My first-author and co-first-author publications appear in Nature Biomedical Engineering, Scientific Data, KDD and PLOS Computational Biology.
Alongside my research, I co-founded Isoplex Intelligence (壹索智能) and serve as CTO, working on scientific agents and research software. More about my industry experience →
Research Interests
Medical AIGenerative Foundation ModelsMedical Image AnalysisDiagnostic ReasoningScientific AgentsSpatial Transcriptomics
Build medical AI and scientific tools that connect research with practice.
Latest News
Recent updates and achievements
Aug 2026
MammoExpert published at KDD 2026
Our mammography reasoning benchmark is published in the KDD 2026 AI4Sciences track. Read Paper →
Apr 2026
BUSGen published in Nature Biomedical Engineering
Our foundation generative model for breast ultrasound image analysis is now published. Read Paper →
Feb 2026
BUS-CoT published in Scientific Data
Our breast ultrasound reasoning dataset covers 99 histopathology categories and includes expert-verified diagnostic annotations. Read Paper →
Apr 2025
Breast tissue classification study published
Our collaborative study of AI-assisted breast ultrasound tissue classification is published in Scientific Reports. Read Paper →
Jan 2025
BUSGen preprint released
The BUSGen preprint introduces a generative model for breast ultrasound image analysis. Read Paper →
Dec 2024
National Digital Health Innovation Competition First Prize
Our team received a national first prize in the 2nd National Digital Health Innovation Application Competition for work on ultrasound-based differentiation of ductal carcinoma in situ and fibroadenoma. Read News →
Oct 2024
National Scholarship Award
I received the National Scholarship at Peking University for the 2023–2024 academic year.
Jul 2024
TAILOR preprint released
Our preprint explores knowledge-driven synthetic data for breast ultrasound diagnosis, including rare cases. Read Paper →
Jun 2024
ST-CellSeg published in PLOS Computational Biology
Our work on multi-scale manifold learning for cell segmentation in imaging-based spatial transcriptomics is published. View Article →
Jul 2023
Featured in University Promotion
Selected as an outstanding student representative for Xi'an Jiaotong University promotion. View Article →
May 2023
Paper Accepted at MICCAI 2023
Early acceptance of our work "Mining Negative Temporal Contexts For False Positive Suppression In Real-Time Ultrasound Lesion Detection". View Article →
Research Highlights
Three connected directions in medical and scientific AI
Diagnostic Reasoning
Structured reasoning datasets and benchmarks that connect imaging observations, clinical features and pathology.
Explore researchScientific Agents
Research workspaces and agent systems that connect literature, data analysis, model development and experimental feedback.
Explore researchHonors & Awards
Selected scholarships and honors
- BYD Scholarship; Merit Student · Peking University 2025–2026
- Huawei Scholarship · Peking University 2024–2025
- National First Prize · 2nd National Digital Health Innovation Application Competition 2024
- National Scholarship; Merit Student · Peking University 2023–2024
- Outstanding Graduate · Xi’an Jiaotong University 2022–2023
- China Scholarship Council & Mitacs scholarships 2021–2022
- MEGVII Scholarship · Xi’an Jiaotong University 2020–2021
- National Scholarship; Merit Student · Xi’an Jiaotong University 2019–2020