Universidad Carlos III de Madrid - UC3M

We have carried out projects in data mining and offered technical and strategic consulting services and prepared viability studies for companies willing to use artificial intelligence in their projects. We have also developed powerful solutions for intelligent control systems, prediction of phyiscal and financial phenomena, optimization systems, and market studies, among others.

M*: Multiobjective Metaheuristics and Multidisciplinar Aplications (2009-2012)

Project Id: TIN2008-06491-C04-04 [Ministry of Science and Innovation (Spain)]

This project is aimed at innovating in multiple fronts of multiobjective optimization (MO) from the perspective of metaheuristic techniques. The main goals in the subproject MSTAR::UC3M are to create a body of knowledge in MO optimization and in applying the resulting techniques to benchmarks and to problems in the context of Economy and Classification: Adaptation of some methods to Multiobjective problems: Adapt some existing techniques to their use in multiobjective problems. This includes Genetic Algorithms, Evolutionary Strategies, Ant Colony Optimization, Particle Swarm Optimization and Estimation Density Algorithms.

OPLINK: Net Centric Optimization (2005-2008)

TIN2005-08818-C04-01 [Ministerio de Educación y Ciencia (Spain)]

This project proposal aims at profiting from the present wealth of advanced knowledge in combinatorial optimization to solve problems of high impact in academics, industry, and society. In a world of high connectivity, networks and communications are worthy fields to make research in, and this is why we target them in this proposal. Our main goal is indeed to detect what are the actual hard problems in the core of different net centric applications, and since most times they are of a combinatorial nature, we propose to use exact, heuristic and in general whatever new technique that may lead to solve them in an efficient and accurate way. By net centric we mean here mobile/ad-hoc network design, mobile and satellite channel/frequency allocation, routing, grid technologies, parallel computing, and related applications.

CECMP: Evolutionary Computation for Classificaciont in Data Mining (2007)

CCG06-UC3M/ESP-0774 [Comunidad Autónoma de Madrid - Universidad Carlos III de Madrid]

The project proposal considered two research lines about using evolutionary computation methods for classification tasks based on the nearest neighbour rule. We use two different novel techniques: in the first, we coevolve of a distance measure for prototypes using a GA; in the second we develop a new approach for the Particle Swarm algorithm where each particle represents a prototype, thus reducing greatly the search space dimension.

TRACER: Advanced Optimisation Techniques for Complex Problems (2002-2004)

TIC2002-04498-C05-02 [Ministerio de Ciencia y Tecnología]

TRACER is an MCyT and FEDER funded project aimed at performing research in computer science with roughly two foci: a. Making advances in modern optimization and search techniques b. Solving complex problems at a higher efficiency and accuracy TRACER is intended to provide concrete results to the community: 1. Software facilities for programmers 2. An Internet front end for non-specialized researcher 3. A web site with problems descriptions and detail 4. A network of thematic mini-web sites on specialized research domains

eInkPllusPlus: Intelligent Digital Content Platform

Project Id: TSI-020110-2009-1374 [Ministry of Science and Innovation (Spain)]

The aim of the project is to develop a platform for Intelligent Digital Content. The project will provide new standards to support the development of Intelligent EBooks, a new way to construct and provide providing Intelligent Content and sharing it automatically by using personalized profiles.

ML-BCI: Machine Learning for Brain Computer Interface (2008)

CCG07-UC3M/ESP-3286 [Comunidad Autónoma de Madrid - Universidad Carlos III de Madrid]

This project belongs to the brain-computer interface (BCI) research field. According to the project proposal, we have developed a tool for aquiring and processing electroencefalographic (EEG) data in real time. It also learns patterns from the EEG data by means of Neural Networks and allows a person to use his thoughts to control a cursor on the screen.

CibMin: Bioinspired Computation for Data Mining (2006)

UC3M-TEC-05-029 [Comunidad Autónoma de Madrid - Universidad Carlos III de Madrid]

This Project is made of two research lines. First, a Genetic Programming engine has been built (GPPE), that projects datasets to spaces of higher or smaller dimension, where classification and regression is easier (cuasi-linear). In the second research line, we have used genetic techniques to evolve regression rules and Particle Swarm Optimisation (PSO). The rules evolved have the property that in addition to obtaining accurate rules, the subspace where each rule is appropriate, is also obtained. Also, the binary PSO for classification rules has been studied, by following an innovative approach where the solution is coded by the whole set of particles (Michigan approach) and not by each one of them (Pittsburg approach).