Itsaso Vitoria is a PhD student at the University of the Basque Country and a researcher at Tecnalia Research and Innovation. Under the supervision of Dr. Ignacio Arganda-Carreras, Dr. Adrian Galdran and Dr. Cristina L. Saratxaga, her research focuses on the application of foundation models for biomedical images, expecting to defend her thesis by the end of 2030. She holds an MSc in Machine Learning for Health (2023) from the University Carlos III of Madrid (UC3M) and a BSc in Biomedical Engineering (2022) from Mondragon University (MU).

Itsaso’s current research explores the integration of foundation models, particularly Vision Transformers (ViTs) and DINO-based architectures, to advance biomedical image analysis. Her previous work has focused on evaluating the efficacy of different foundation models as encoders within U-Net-like architectures for dense prediction tasks, specifically targeting biomedical image segmentation.

With extensive experience in managing large-scale biomedical datasets, she has worked across diverse modalities, including CT, histopathology, and microscopy. She is currently contributing to several high-impact projects focused on AI-driven clinical decision support, synthetic healthcare data, and the analysis of embryos and lung evolution.