Jéssica Catarino, MSc, is a PhD student at the Faculty of Sciences, University of Lisbon, conducting her research in collaboration with the Champalimaud Foundation, where she has been involved in breast cancer imaging research since 2020. Her doctoral work focuses on leveraging Self-Supervised Learning to enhance breast cancer diagnosis through Deep Learning segmentation of breast imaging data.

By enabling computational models to learn from unlabeled data and generalize across imaging modalities, vendors, and populations, her research aims to reduce reliance on large annotated datasets—addressing a significant challenge in clinical Artificial Intelligence. Her work also includes clustering and outlier detection to manage model uncertainty better, ultimately contributing to developing more accurate and scalable diagnostic tools in oncology.