Faisal Mahmood
费萨尔·马哈茂德
PhD
Associate Professor of Pathology; Director, Computational Pathology & AI Lab病理学副教授；计算病理学与AI实验室主任
👥Biography 个人简介
Faisal Mahmood leads the Computational Pathology and AI Lab at Harvard/BWH, pioneering large-scale foundation models for digital pathology. He created CONCH (pathology-language vision model) and UNI (universal pathology encoder), which have become benchmark models for cancer diagnosis, subtyping, and prognosis from whole-slide images globally.
🧪Research Fields 研究领域
🎓Key Contributions 主要贡献
CONCH & UNI Foundation Models
Developed CONCH and UNI, large-scale vision-language and vision foundation models trained on millions of pathology image-text pairs, enabling state-of-the-art cancer diagnosis and subtyping.
Weakly Supervised Pathology AI
Pioneered attention-based multiple instance learning frameworks (CLAM) for weakly supervised whole-slide image classification, widely adopted in computational pathology research worldwide.
Representative Works 代表性著作
A Pathology Foundation Model for Cancer Diagnosis and Prognosis Prediction (UNI)
Nature Medicine (2024)
UNI, a universal pathology encoder, achieves state-of-the-art performance across 34 computational pathology tasks.
CONCH: A Vision-Language Foundation Model for Computational Pathology
Nature Methods (2024)
Vision-language model trained on 1.17M pathology image-caption pairs enabling zero-shot cancer classification.
🏆Awards & Recognition 奖项与荣誉
📄Data Sources 数据来源
Last updated: 2026-01-15 | All information from publicly available academic sources
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