The Computational Intelligence Group (CIG) was created in 2008 and is lead by professors Pedro Larrañaga and Concha Bielza. Research of CIG members, both theoretical and practical, is devoted to modelization (from a statistical and machine learning perspectives), heuristic optimization, and neuroinformatics.
The main research area is modelization, whose current main issues include: data streams, multi-dimensional supervised classification, multi-label classification, clustering in high-dimensional spaces, feature subset selection using methods as Bayesian networks, regularization, classification by regression.
In heuristic optimization, which is the second main line of research, we investigate state-of-the-art questions related to the improvement of heuristic optimization methods and extension of their applicability to more complex problems (e.g. multi-objective, mixed representation, non-continuous objective functions), with special emphasis on estimation of distribution algorithms.
Neuroscience is the main field of application. Some problems that we face include: (a) neuroanatomy issues, like modeling and simulation of dendritic trees and classification of neuron types based on morphological features; (b) neurodegenerative diseases, like predicting health-related quality of life in Parkinson's disease and searching for genetic biomarkers in Alzheimer's disease.
The second main field of application is Industry 4.0 where we develop machine learning solutions for cyber-physical systems. Other application domains are: biomedicine, agriculture, bioinformatics, bibliometry and environment.
CIG has been involved in more than 70 research projects, mostly in public competitive calls but also for private companies. Current public projects include Human Brain Project, Cajal Blue Brain and several national projects from the Spanish Ministry of Science and Innovation. CIG has collaborated with companies as Telefónica I+D, Abbott, Arthur Andersen, Progenika Biopharma, Bank of Santander and Panda Security.