Research Areas
Here you will find a brief description of each research area
Pharmacoinformatics
Chemoinformatics uses computational techniques such as Machine Learning, Deep Learning, QSAR, or Docking to obtain solutions in the search for new drugs and molecular targets for the treatment of diseases. To achieve this, a multidisciplinary approach is required that combines the fields of health—such as chemistry, pharmacology, and biology—with those of technology, such as computing and artificial intelligence.
Information Security and Protection Line. Cyber Defense and Forensics
We can say that without risk there is no fun. But, as in the rest of life’s facets, risks must be controlled and security mechanisms implemented to prevent fun from turning into failure. Information and communication technologies are not exempt, and our world is full of risks—good and bad, bad ones that seem good, and good ones that are not.
E-learning and Technological Design
In this line of work, the focus is mainly on aspects of human–machine interaction. On the one hand, it seeks to improve distance learning methods with the aim of facilitating learning: new interfaces, active learning methodologies, inclusion of social networks, gamification, etc. On the other hand, it aims to incorporate advances in computing and object design toward intelligent environments with a certain degree of autonomy, known as ambient intelligence.
Evolutionary Computing and Artificial Intelligence in Civil Engineering
Advances in the field of Artificial Intelligence have had a strong influence on the different areas of Civil Engineering. For this reason, this line of work uses new methods, techniques, and Artificial Intelligence algorithms in various fields of civil engineering such as Construction, Hydrology, and Ports and Coastal Engineering.
Connectionist Computational Modeling: Artificial Intelligence and Neuroscience
Artificial Intelligence proposes computational models inspired by the information processing systems of intelligent beings. Neuroscience, in order to advance, requires the use of Artificial Intelligence models and techniques to validate discoveries and test hypotheses proposed in neuroscience laboratories, aiming to understand how information is intrinsically processed in the brain.
Bioinformática e Minería de Datos. Gráficos e procesamento de imaxe
O grupo RNASA-IMEDIR presenta unha gran experiencia na aplicación de varias técnicas de Intelixencia Artificial: Redes de Neuronas Artificiais, Sistemas Evolutivos, Sistemas Expertos…
A transferencia destes métodos ao ámbito práctico faise especialmente relevante na liña de ‘datamining’, procesado de imaxe e bioinformática. Debido á especial natureza e heteroxeneidade dos datos cos que se traballa adoita ser necesario o traballo conxunto de diferentes técnicas e/ou a realización de rigorosos controis estadísticos que permitan determinar o mellor dos métodos.
Accesibilidade, TIC en diversidade funcional e envellecemento
Aplicación das tecnoloxías da información e as comunicacións no ámbito da discapacidade. Adaptación do ordenador mediante o deseño e desenvolvemento de productos de apoio e adaptaciones. Creación de contidos multimedia para a intervención desde terapia ocupacional. Evaluación do impacto de programas basados no uso das TIC nas persoas maiores e/ou con discapacidade utilizando diferentes instrumentos de valoración.
Aprendizaje Automático Avanzado y Optimización Inteligente para Sistemas Complejos (A³O-Intelligence)
The research line in Advanced Machine Learning and Intelligent Optimization for Complex Systems (A³O-Intelligence) focuses on the development, analysis, and application of machine learning techniques and optimization methods based on artificial intelligence to address real-world challenges across multiple domains
Informática Médica e Ontoloxías
A mediciña participativa basa o seu principio en cambiar a relación médico-paciente mediante unha nova relación de equipo. O cidadá autorresponsabilízase de obter datos da súa saúde mediante dispositivos ‘poñibles’ (wearable) e compárteos co médico para que, conxuntamente, analicen os datos e o médico identifique o significado. Faise copartícipe ao cidadá das decisións e da responsabilidade do tratamento. Neste ámbito, desde o grupo de investigación, trabállase en crear a infraestructura tecnolóxica que de soporte a este novo enfoque da mediciña, facilitando a integración dos datos e a comunicación entre participantes.
