Departamento de Ciencias de la Computación e Inteligencia Artificial

Bioinspired computation

Since the beginning of my career as researcher, I've been working with bioinspired computation (neural networks, genetic algorithms, et.c). I've been developing hybrid training methods for artificial neural networks and their application to different problems such as time series prediction, estimation of chemical parameters, ADN pattern recognition, between others. More specifically, my interests are:

  • Fuzzy/Crisp grammatical inference using Recurrent neural networks
  • Hybrid algorithms to improve the learning of neural networks
  • Multi-objective optimization
  • Fuzzy rules extraction from neural networks
  • Time series prediction
  • Sensor technologies to solve imprecise optimization and classification problems
  • Fuzzy neural networks
  • Evolutionary algorithms for grammatical inference
  • Evolutionary training of neural networks
  • Neural networks and evolutionary algorithms for pattern recognition
  • Genetic algorithms for solving problems with imprecise information
  • Genetic algorithms for design and identification of fuzzy systems