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 leader
Miguel Ángel Sicilia Urbán
+34-918856640
Principal Investigator
- Marçal Mora Cantallops
- Juan José de Lucio Fernández
Collaborating Staff
- María Elena García Barriocanal
- Salvador Sánchez Alonso
- Ángel Luis del Rey Mejias
- Diego Cárdenas Cuadrado
- Samuel Santos Benito
- Sergio Moreno Solera
- Hilario Gómez Moreno
- Fernando Cruz Roldán
- Manuel Blanco Velasco
- María Mercedes Rodríguez García
- Alberto Ballesteros Rodríguez
Principal Investigator
- Marçal Mora Cantallops
- Juan José de Lucio Fernández
Collaborating Staff
- María Elena García Barriocanal
- Salvador Sánchez Alonso
- Ángel Luis del Rey Mejias
- Diego Cárdenas Cuadrado
- Samuel Santos Benito
- Sergio Moreno Solera
- Hilario Gómez Moreno
- Fernando Cruz Roldán
- Manuel Blanco Velasco
- María Mercedes Rodríguez García
- Alberto Ballesteros Rodríguez
Strategic objectives
- Develop and apply data science methods and techniques to biomedical research problems and challenges.
- Apply new or existing Artificial Intelligence (AI) techniques and methods to biomedical problems and data, based on biomedical research results.
- Apply and develop techniques for processing complex data and large volumes of biomedical data, including privacy-preserving analytics or machine learning.
- Design and evaluate the integration, interoperability and quality management of biomedical data by applying data engineering techniques.
- Evaluate and incorporate in the design of systems and models the Trustworthy AI approach according to best practices and European regulation
Research lines
- Design and development of Artificial Intelligence models and systems in biomedicine, covering all domains, types of data and techniques.
- Use of computational and simulation methods applied to biomedicine.
- Biomedical data processing and data engineering in biomedicine.
- Technological tools and innovative methods in data collection, visualisation and decision support systems.
Location
Hospital Universitario Ramón y Cajal. Data Science Unit. Floor: -3D
Phone: +34-918856640
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E-mail: msicilia@uah.es |
Keywords
Data Science, Data Engineering, Artificial Intelligence, Computational Methods, Trustworthy AI, Big Data