Biomedical Data Science and Engineering
The Biomedical Data Science and Engineering group aims to research and apply computational methods to all kinds of problems in biomedical contexts, especially focused on Artificial Intelligence (AI), covering every machine learning technique, as well as any type of data, from images to natural language. The group has a transversal approach, seeking active collaboration with the rest of the Institute's groups and other external actors, and working with a direct involvement with the Data Science Unit (DSU) to facilitate the transfer of results to clinical practice and innovation in products and services.
2025 ACTIVITY INDICATORS
- 2 European projects: PRIV-FHE-VC (FSTP-HE) and TechConnect (HE)
- 1 competitive national public project: FECYT
- 1 publication
- IF: 2.40
- 2 doctoral theses supervised and defended
- Evaluators of scientific articles and individual applications for research staff at different institutions: 2 PI
- Members of editorial committees: 2 researchers
- 1 visiting researcher and 1.6-month stay: Polytechnic University of Madrid
Milestones
- Kick-off of the European project AIMS (Artificial Intelligence for Medical Students) under the Erasmus+ program, aimed at integrating practical and ethical AI skills into medical training at the European level.
- Completion of the TRITON-DMP project, focused on the selection, validation, and implementation of tools for managing research data plans and catalogs.
- Completion of the PRIV-FHE-VC project, focused on developing predictive models in health while preserving privacy through Fully Homomorphic Encryption and Verifiable Credentials. FSTP support within the European project SECURED-101095717 (Cluster Health - HE)
- Release of the madmpy library, a Python solution for the automated creation and validation of Data Management Plans (DMPs)
- Participation in a program with OpenMined to test secure computing technologies on distributed data.
