Faisal Mahmood
Director, MGB Center For AI Research at Harvard Medical School
Boston, Massachusetts, United States
Summary
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Rockstar🎓
Top SchoolFaisal Mahmood is a computational pathology and AI leader with seven years of experience advancing medical imaging research at top institutions, now serving as Director of the MGB Center for AI Research. As an Associate Professor at Harvard Medical School and Lead Investigator at Brigham and Women's Hospital, he translates deep learning methods into clinical-grade tools for histopathology, biomarker discovery, and endoscopic imaging. His background spans PhD-level biomedical imaging, postdoctoral work in deep learning for medical images at Johns Hopkins, and cross-disciplinary stints at the Broad Institute and Dana‑Farber, reflecting a rare blend of academic rigor and translational focus. Mahmood combines hands-on technical depth in imaging, domain adaptation, and model interpretability with leadership in building research teams and centers. He is active in the scientific community (Mahmood Lab) and shares insights publicly via X (@AI4Pathology), signaling a commitment to open science and clinical impact.
7 years of coding experience
9 years of employment as a software developer
Johns Hopkins UniversityExchange Student Analog & Digital IC Design, Exchange Student Analog & Digital IC Design at Imperial College LondonDoctor of Philosophy (PhD) Biomedical Imaging, Doctor of Philosophy (PhD) Biomedical Imaging at Okinawa Institute of Science and TechnologyCORe: Credential of Readiness, CORe: Credential of Readiness at Harvard Business SchoolMachine Learning Summer School (MLSS), Machine Learning Summer School (MLSS) at Max Planck Society
Github Skills (49)
data-efficient10
histopathology10
slide10
cgan10
image-retrieval10
fusion10
ieee10
transcriptomics10
deep-learning10
segmentation10
clam10
digital-pathology10
biomedical-engineering10
genomics10
weakly-supervised-learning10
Programming languages (2)
Github contributions (5)
mahmoodlab/CLAM
May 2020 - Mar 2022
Open source tools for computational pathology - Nature BME
Contributions:16 commits, 21 pushes, 1 comment in 1 year 10 months
engineeringhistopathologybiomedical-engineeringtcga-datacamelyon16
mahmoodlab/HistoFL
May 2021 - Dec 2021
Federated Learning for Computational Pathology - Medical Image Analysis
Contributions:8 commits, 6 pushes in 7 months
medical-imagemedicalvtkconnectivityneuroimaging
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