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.
Group leaders
Miguel Ángel Sicilia Urbán
Alberto Nogales Moyano
+34-918856640
Principal Investigator
- Marçal Mora Cantallops
- Juan José de Lucio Fernández
- María Elena García Barriocanal
Collaborating Staff
- Salvador Sánchez Alonso
- Ángel Luis del Rey Mejias
- Diego Cárdenas Cuadrado
- Samuel Santos Benito
- Hilario Gómez Moreno
- Fernando Cruz Roldán
- Manuel Blanco Velasco
- María Mercedes Rodríguez García
- Lino González García
- Antonello Conelli
- David Santamaría Santamaría
Group leaders
Miguel Ángel Sicilia Urbán
Alberto Nogales Moyano
+34-918856640
Principal Investigator
- Marçal Mora Cantallops
- Juan José de Lucio Fernández
- María Elena García Barriocanal
Collaborating Staff
- Salvador Sánchez Alonso
- Ángel Luis del Rey Mejias
- Diego Cárdenas Cuadrado
- Samuel Santos Benito
- Hilario Gómez Moreno
- Fernando Cruz Roldán
- Manuel Blanco Velasco
- María Mercedes Rodríguez García
- Lino González García
- Antonello Conelli
- David Santamaría Santamaría
Strategic objectives
- Develop and apply data science methods and techniques to problems and challenges in biomedical research.
- Apply new or existing Artificial Intelligence (AI) techniques and methods to biomedical problems and data, based on the results of biomedical research.
- Apply and develop techniques for processing complex data and large volumes of biomedical data, including analytics and machine learning, while preserving privacy.
- Design and evaluate the integration, interoperability, and quality management of biomedical data using data engineering techniques.
- Evaluate and incorporate the Trustworthy AI approach into the design of systems and models, in accordance with best practices and European regulations.
Research lines
- Design and development of artificial intelligence models and systems in biomedicine, encompassing all domains, data types, and techniques.
- Use of computational and simulation methods applied to biomedicine.
- Biomedical data processing and data engineering in biomedicine.
- Technological tools and innovative methods for data collection, visualization, and decision support systems.
Location
Ramón y Cajal University Hospital
Data Science Unit
Floor -3 Right
Keywords
Data science, data engineering, artificial intelligence, computational methods, trustworthy AI, big data