# Faisal Mahmood

Source: https://onco.cc/people/faisal-mahmood/  
OnCo record `faisal-mahmood` (Person). Data CC BY-NC 4.0, attribute "Data from OnCo (onco.cc)"; commercial use needs a licence.

## TL;DR

Built UNI and CONCH, the pathology foundation models that let AI read whole-slide images across cancer types.

## Summary

Faisal Mahmood's laboratory developed CLAM for weakly supervised whole-slide learning, TOAD for predicting tumour origin, and the UNI and CONCH foundation models trained on more than 100 million pathology images, which set the benchmark for general-purpose computational pathology. His group also builds multimodal models integrating histology with genomics for prognosis and is a leading academic voice on AI in pathology.

## Fields

- Kind: Person
- Last checked: 2026-09-10
- Tags: ai; pathology; foundation-models
- Role: Associate Professor of Pathology, Harvard Medical School and Brigham and Women's Hospital; Associate Member, Broad Institute
- Specialisms: Computational pathology; Pathology foundation models; Multimodal AI; Weakly supervised learning

## Sources

- PubMed: https://pubmed.ncbi.nlm.nih.gov/?term=Mahmood%20F%5BAuthor%5D%20computational%20pathology

## Connected records

- technologies: [Digital pathology & AI](https://onco.cc/technologies/digital-pathology-ai/), [Pathology & radiology foundation models](https://onco.cc/technologies/pathology-foundation-model/)
- institutions: [Broad Institute of MIT and Harvard](https://onco.cc/institutions/broad-institute/)
- key papers: [AlphaFold 2: predicting protein structures to near-experimental accuracy](https://onco.cc/key-papers/paper-alphafold2-jumper-nature-2021/)

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