Dr. Rafael Dias is a Senior AI Engineer on Foundational Models for Healthcare, with a strong background in Machine Learning, including both industry and academic experience. He holds a PhD in Machine Learning applied to Astrophysics and has over a decade of professional experience in Python programming. His scientific contributions include authoring ML book chapters and articles in Q1 journals. Dr. Dias is pioneering the development and deployment of advanced AI tools in collaboration with NHS Trusts, universities, and industry partners to enhance clinical decision-making and improve patient care pathways. He has been instrumental in the success of the Federated Learning Interoperability Platform (FLIP), a multi-NHS Trust data connectivity platform designed for scalable and privacy-preserving AI development. A core focus of his work involves leading the development of novel vision-language foundational models by integrating medical imaging (X-rays, CT, MRIs) with radiological reports. This work is enabling critical downstream applications such as automated report generation, image synthesis from reports, and discrepancy identification between reports and scans. He also contributes to prominent open-source projects like MONAI Core.