Carlos Aguirre Maeso holds a Bc in Mathematical Sciences from Universidad Autónoma de Madrid and a PhD in Computer Science from that university with the qualification of Outstanding cum Laude. The research developed focuses initially on the field of expert systems and artificial intelligence and later on in the field of complex networks as well as non-linear dynamics, numerical methods and data analysis and Deep Learing. The research work has resulted in a total of twenty-three publications in international journals and a book of scientific nature, as well as different contributions to national and international conferences. Part of the research work has been carried out in several prestigious international centers such as the Institute of Nonlinear Science of the University of San Diego and the Supercomputer Center of the University of San Diego (USA), the Zentrum fur Interdisziplinare Forschung (ZIF), the University of Bielefeld (Germany) and the Interdisciplinary Complex of the Universidade de Lisboa (Portugal), in addition to research stays both pre and post doctoral in the aforementioned centers.


  • • “Signal-adapted tomography as a tool for dust devil detection”; Aguirre, C.; Franzese, G.; Esposito, F.; et al., Aeolian Research Volume: 2017
  • • “Mathematics and Mars Exploration”; Velasco, M. P.; Usero, D.; Jimenez, S.; et al. , Pure and Applied Geophysics 2015
  • • “Signal recognition and adapted filtering by non-commutative tomography”; Aguirre, C.; Vilela Mendes, R., IET Signal Processing 2014
  • • “Transient dynamics and rhythm coordination of inferior olive spatio-temporal patterns”; Latorre, Roberto; Aguirre, Carlos; Rabinovich, Mikhail I.; et al. , Frontiers in Neural Circuits 2013
  • • “Single Neuron Transient Activity Detection by Means of Tomography” ; Aguirre, C.; Pascual, P.; Campos, D.; et al. , Advances in Computational Intelligence. Proceedings of the 11th International Work-Conference on Artificial Neural Networks, IWANN 2011
  • • “A Wavelet Based Method for Detecting Multiple Encoding Rhythms in Neural Networks” ; Aguirre, Carlos; Pascual, Pedro , Bio-Inspired Systems: Computational and Ambient Intelligence, 2009
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