Multi-modal Modeling in Precision Medicine: From Data Imputation to Synthetic Data
Data Science Seminar Series
March 18, 2026 | 11:00 AM – 12:00 PM
Online
Join Stanford Medicine’s Dr. Olivier Gevaert as he introduces the concept of cross-modal data modeling—a methodology that uses foundation models (i.e., large, pre-trained, artificial intelligence models) to ascribe missing biomedical research data and generate realistic synthetic samples.
He’ll highlight:
- how cross-modal data modeling uses one data type (like imaging) to fill in gaps in another data type (like genomics).
- ongoing multi-modal modeling efforts in spatial omics, digital pathology, and radiology.
- how multi-modal modeling is anticipated to help us better understand disease biology and improve healthcare practices.
Multi-modal modeling can empower researchers, like you, to model complex interactions among diverse biomedical data types (including omics and imaging). This approach can illuminate how one modality influences another, facilitating in-silico exploration of disease mechanisms without the need for extensive and costly real-world data collection.
About the Speaker
Olivier Gevaert, Ph.D.
Dr. Gevaert is an associate professor at Stanford University and has a lab within the Stanford Center for Biomedical Informatics Research. His research focuses on multi-scale biomedical data fusion in oncology and neuroscience. The lab develops both machine and deep learning methods to integrate molecular data or omics data, and the lab investigates linking omics data with cellular and tissue data in the context of computational pathology, imaging genomics, and radio-genomics.
About the Data Science Seminar Series
CBIIT’s Data Science Seminar Series is dedicating its 2026 events to spotlighting the use of AI in cancer research and care. Brought to you by CBIIT and NCI’s Division of Cancer Treatment and Diagnosis AI working group, the upcoming webinars will explore a variety of questions, such as the following:
- How can AI be used for diagnosis, treatment, or omics research?
- What are the related laws and ethical considerations for AI?
- How can we empower an AI-ready cancer research community through workforce development, collaborations, and funding?
To view upcoming speakers or recordings of past presentations, visit the Data Science Seminar Series page.