Inés María Galván León

Inés María Galván León

Contact Info

Inés María
Galván León
Profesor Titular
Ciencia de la Computación e Inteligencia Artificial

Curriculum Vitae

Formación académica

  • Licenciada en Matemáticas, Facultad de Matemáticas, Universidad de Sevilla, 1989
  • Doctora en Informática, Facultad de Informática, Universidad Politécnica de Madrid, 1998

Proyectos de Investigación

  • SEACW: Social Ecosystem for anti-aging, capacitation and wellbeing (RTD). 2013-2015

  • Gestión de Movilidad Eficiente y Sostenible: MOVES (TIN2011-28336), 2012-2014

  • M*: Metaheurísticas Multiobjetivo y Aplicaciones Multidisciplinares, Ministerio de Educación y Ciencia, 2008-2011
  • OPLINK: Optimización y Ambientes de Red, Ministerio de Educación y Ciencia, 2005-2008
  • Diseño automático de programas de control secuencial: aplicación al control de procesos térmicos en la industria láctea, Ministerio de Educación y Ciencia (CICYT), 2000- 2002
  • Control and malfunction diagnosis in batch chemical reactors using neural networks, European Commission, 1992-1995


Publicaciones más relevantes

Martin, R., Aler, R., Valls, J. M., & Galvan, I. M. (2015). Machine learning techniques for daily solar energy prediction and interpolation using numerical weather models. Concurrency and Computation: Practice and Experience. En prensa

Ricardo Aler and Inés M. Galván. Optimizing the Number of Electrodes and Spatial Filters for Brain-Computer Interfaces by means of an Evolutionary Multi-objective Approach. Expert System with Applications. 2015. 42(15), 6215-6223

García-Cuesta, E., de Castro, A. J., Galván, I. M., & López, F. Temperature Profile Retrieval in Axisymmetric Combustion Plumes Using Multilayer Perceptron Modeling and Spectral Feature Selection in the Infrared CO2 Emission Band. Applied spectroscopy, 68(8), 900-908.  2014

Sandra García, David Quintana , Inés M. Galván and Pedro Isasi. Extended mean–variance model for reliable evolutionary portfolio optimization. AI Communications 27 (2014) 315–324 315

Garcia S., Quintana D., Galván. I. and, Isasi P. Multiobjective Algorithms with Resampling for Portfolio Optimization. Computing and informatics.  Vol. 32, 2013, No. 4, pp. 777–796

Ricardo Aler, Inés M. Galván, José M. Valls. Applying evolution strategies to preprocessing EEG signals for brain–computer interfaces .Information Sciences 215 (2012) 53–66.  (JRC-2011): 2.833 T1

Garcia S., Quintana D., Galván. I. and, Isasi P..Time-stamped Resampling for Robust Evolutionary Portfolio Optimization  Expert Systems with Applications, 39(12), 10722-10730, 2012. (JRC-2011):2.203 T1

Ricardo Aler, Alicia Vega, Inés M. Galván and Antonio J. Nebro. Multi-objective metaheuristics for preprocessing EEG data in brain–computer interfaces. Engineering optimization, Vol.44, No.3 (March 2012), pp. 373–390. (JRC-2011): 0.936 T2

Inés M. Galván, Joś M. Valls, Miguel García and Pedro Isasi. A lazy learning approach for building classification models . Internacional Journal of Intelligent Systems, Volume 26, Issue 8 (2011) (pages 773–786).  (JRC-2011): 1.653 T2

Esteban Garcia-Cuesta, Inés M. Galvan, and Antonio J. de Castro. Recursive Discriminant Regression Analysis to Find Homogeneous Structures. Internacional Journal of Neural Systems, Vol. 21, No. 1 (2011) 1–7.(JRC-2011): 4.284 T1

Alejandro Cervantes, Inés M. Galván and Pedro Isasi. AMPSO: A new Particle Swarm Method for Nearest Neighborhood Classification. IEEE Transactions on Systems, Man, and Cybernetics: Part B. vol. 39, n. 5, Oct. 2009, p. 1082 – 1091.  (JRC-2009): 3.007 T1

A. CERVANTES and I. GALVAN and P. ISASI. Michigan Particle Swarm Optimization for Prototype Reduction in Classification Problems. New Generation Computing. Vol. 27. Number 3. pp 239-257. 2009. (JRC-2009): 0.364 T3

José M. Valls,, Inés M. Galván  and Pedro Isasi. Learning radial basis neural networks in a lazy way: A comparative study. Neurocomputing, Volume 71, Issues 13-15, August 2008, Pages 2529-2537. (JRC-2008):  1.234 T2

Esteban García-Cuesta, Inés M. Galván and Antonio J. de Castro. Multilayer Perceptron as Inverse Model in a Ground-Based Remote Sensing Temperature Retrieval Problem. Engineering Applications of Artificial Intelligence, 2, 26–34 Fecha: 2008. (JRC-2008): 1.397  T1

José M. Valls, Inés M. Galván, Pedro Isasi. LRBNN: A Lazy RBNN Model. AI Communications,  Volumen: 20, Number 2 / 2007. pp 71--86    Fecha: 2007.  (JRC-2007):  0.585 T3

JM Valls., Galván, I., Isasi P. Improving the generalization ability of RBNN using a selective strategy based on the Gaussian Kernel functions. Computers and Informatics, Volumen: 25     1- 15 Fecha: 2006 . (JRC-2005): 0.091 T3

A.Cervantes, A., Galván, I., Isasi P. Binary particle swarm optimization in classification. Neural Network World, Volumen: 15, 229- 241 Fecha: 2005

G. Gutiérrez, A. Sanchis, P. Isasi, J.M. Molina and I. M. Galván. Non-direct Encoding method based on Cellular Automata to design Neural Network Architectures. Computer and Informatics Volumen: 24, Nº 3. 225-247      Fecha: 2005.  (JRC-2004): 0.456; (JRC-2005): 0.091 T3

José M. Valls, Inés M. Galván, Pedro Isasi. Lazy learning in Radial Basis Neural Networks: a way of achieving more accurate models. Neural Processing Letters, Volumen: 20-2, 105- 124 Fecha: 2004. (JRC-2003): 0.631; (JRC-2004): 0.605 T2

J. M. Molina, I.M. Galván, J.M. Valls and A. Leal. Optimizing the Number of Learning Cycles in the Design of Radial Basis Neural Networks. Computing and Informatics Volumen: 20, 429- 449            Fecha: 2001.  (JRC-2000): 0.226 T3

I.  M. Galván, P. Isasi,R. Aler and J. M. Valls. A Selective Learning Method to Improve the Generalization of Multilayer Feedforward Neural Networks. International Journal of Neural Systems Volumen: 11, 167- 157 Fecha: 2001.

I.M. Galván and P. Isasi. Multi-step learning rule for recurrent neural models: An application to time series forecasting. Neural Processing Letters, Volumen: 13, 115-133 Fecha: 2001. (JRC-2000): 0.365; (JRC-2001):  0.379 T2

I.M. Galván, P. Isasi and J. M. Zaldívar.  PNNARMA model: an alternative to phenomenological models in chemical reactors. Engineering Applications of Artificial Intelligence, Volumen 14, 139-154 Fecha: 2001 (JRC-2001): 0.306 T2

J. M. Zaldívar, E Gutiérrez, I.M. Galván, F. Strozzi and A, Tomasin. Forecasting high waters at Venice Lagoon using Chaotic time series analisys and nonlinear neural netwoks. Journal of Hydroinformatics, Volumen: 02.1, 61- 84 Fecha: 2000

I. M. Galván and J.M. Zaldívar. Applications of recurrent neural networks in Bath Reactors. Part II: Nonlinaer inverse and predictive control of the heat transfer fluid temperature. Chemical Engineering and Processing, Volumen: 37, 161-175 Fecha: 1997 (JRC-1997):  0.292. T2

I. M. Galván and J.M. Zaldívar. Applications of recurrent neural networks in Bath Reactors. Part I: NARMA modelling of the dynamic behaviour of the heat transfer fluid. Chemical Engineering and Processing, Volumen: 36, 505- 518            Fecha: 1997. (JRC-1997):  0.292. T2

I.M. Galván, J.M. Zaldívar, H. Hernández and E. Molga. The use of neural networks for fitting complex kinetic data. Computer and Chemical Engineering, Volumen: 20, 1451-1465 Fecha: 1996 (JRC-1996): 0.703 T2

Research Themes

  • Aprendizaje Automático / Minería de Datos
  • Redes Neuronales Artificiales
  • Computación evolutiva
  • Optimización Multi-objetivo
  • Energías Renovables: Solar


Grado en Informática: Redes de Neuronas Artificiales

Master Universitario en Ingeniería Informática: Métodos de Modelado y Simulación por Computador
Máster en Ciencia y Tecnología Informática: Técnicas de Inteligencia Artificial con Inspiración Biológica


Paloma Martínez Fernández


Assistants principal:

Carlos Linares López

Israel González Carrasco

Juan Manuel Estévez Tapiador


Academic Secretary:

Lourdes Moreno López


Secretaría Administrativa:

María José Cano Barquilla

Javier Delicado Huelva

Rafaela Jiménez Mejías


Phone numbers:

+34 91 6249960

+34 91 6249049


Postal Address:

Avda. de la Universidad Nº 30

Edificio Sabatini 28911

Leganés (Madrid) SPAIN


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