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Microscopy images are not just "pretty pictures." Rather, they hold quantifiable data that can be analyzed through image processing techniques, increasingly powered by Artificial Intelligence and Machine Learning (AI/ML). The success of these quantitative methods relies on the availability, propagation, and management of essential Image Metadata. Image credit: Nature Methods Focus Issue on Reporting and Reproducibility for Light Microscopy.

Welcome to the Strambio-De-Castillia lab website

We are in the Program in Molecular Medicine Department at UMass Chan Medical School. Our laboratory develops metadata standards, file formats, software tools, and training strategies to promote imaging data's quality, reproducibility, and sharing value. 

This picture shows Alex Rigano and Caterina Strambio De Castillia
Our passion is to develop user-friendly software tools to advance biomedical research through FAIR Research Data Management and Sharing!

What do we do?

Our research centers on Research Data Management and Sharing (RDMS) for image data, which presents significant potential to drive progress in biomedical science and clinical medicine.

Our lab investigates the application of RDMS technologies across diverse systems, with a particular focus on methods that improve the management and distribution of experimental datasets to support open science initiatives.