Big Data & Bioengineering

The team do research mainly on highly sensitive sensor and technical platforms for thin-film and biological substance characterisation using metamaterials, metasurfaces and plasmonic structures. The characterisation is multispectral, that is, it covers the entire infrared spectrum, from the terahertz band or far infrared to the visible infrared, including mid infrared and near infrared.

The Algebra and Applications multidisciplinary research team is made up of mathematicians and telecommunications engineers. At present, their lines of research are centred on the development of theoretical methods for gathering information based on data from different sources. They develop techniques and algorithms that are used in fields such as biomedical data classification, medical decision making, and evaluation and classification of movements in people with motor disabilities or the elderly.

Lines of research:

• Machine-learning methods for multimodal information extraction.
• Multimodal analysis of human movement. Application to rehabilitation and functional capacity improvement.
• Techniques for optimising information extraction from clinical signs obtained with non-invasive techniques.
• Group theory. Aggregation and engagement: application to data classification and decision-making under uncertainty.

The Artificial Intelligence and Approximate Reasoning Group (GIARA) was established in 2002 by Professor Humberto Bustince at the Public University of Navarra. Currently, GIARA is made of eighteen members (twelve holding doctoral degrees and five doctoral students).
GIARA is a multidisciplinary team (physicists, mathematicians, computer engineers and industrial engineers) with broad experience and a remarkable national and international impact. They conduct theoretical research in the areas of information fusion, fuzzy sets and extensions. In addition, they develop models and applications in the fields of data mining, big data and image processing.

Lines of research:

• Theory: information fusion, fuzzy sets and extensions.
• Decision making: multicriteria, consensus, preference relations and recommendation systems.
• Computer vision: image processing, magnification/demagnification, edge detection, stereo vision.
• Data mining: machine learning, classification, fuzzy rule-based models, ensemble-based models, deep learning, big data.