Olivier Gevaert

Olivier Gevaert, PhD is Associate Professor in the Department of Medicine and Department of Biomedical Data Science at Stanford University, where he directs the imaging informatics program within the Stanford Center for Biomedical Informatics Research (BMIR). Dr. Gevaert is a pioneer in radiogenomics — the field integrating radiological imaging features with genomic and molecular profiles to discover imaging biomarkers that reflect tumor biology. His laboratory develops machine learning models that extract quantitative imaging features (radiomic and deep learning features) from CT, MRI, and PET scans and link them to gene expression signatures, copy number alterations, somatic mutations, and clinical outcomes, enabling non-invasive molecular tumor characterization from standard-of-care imaging. Dr. Gevaert has been a major contributor to The Cancer Imaging Archive (TCIA), the NCI-sponsored public imaging data repository, where he has led data curation and analysis efforts for multiple cancer imaging-omics datasets that are now widely used by the computational oncology community. His group has published multimodal AI frameworks for glioblastoma, lung, breast, and ovarian cancer, demonstrating that imaging-genomics integration improves prognostic accuracy beyond either modality alone. He has also contributed methodological advances in transfer learning, graph neural networks, and interpretable AI for radiology.