Results

Research articles

Orozco Valero, A., Rodríguez-González, V., Montobbio, N., Casal, M. A., Tlaie, A., Pelayo, F., ... & Martínez-Cañada, P. (2025). A Python toolbox for neural circuit parameter inference. npj Systems Biology and Applications, 11(1), 1-17. https://doi.org/10.1038/s41540-025-00527-9 

Gómez-López, J. C., Rodríguez-Álvarez, M., Castillo-Secilla, D., & González, J. (2025). Tuning multi-objective multi-population evolutionary models for high-dimensional problems: The case of the migration process. Neurocomputing, 130631. https://doi.org/10.1016/j.neucom.2025.130631 

Escobar, J. J., Sánchez-Cuevas, P., Prieto, B., Kızıltepe, R. S., Díaz-del-Río, F., & Kimovski, D. (2025). Energy–time modelling of distributed multi-population genetic algorithms with dynamic workload in HPC clusters. Future Generation Computer Systems, 167, 107753. https://doi.org/10.1016/j.future.2025.107753 

Montobbio, N., Maffulli, R., Abrol, A., Martínez-Cañada, P. (2024). Editorial: Computational Modeling and Machine Learning Methods in Neurodevelopment and Neurodegeneration: from Basic Research to Clinical Applications. Frontiers in Computational Neuroscience 18. https://doi.org/10.3389/fncom.2024.1514220  

Prieto, A., Prieto, B., Escobar, J.J., & Lampert, T. (2024). Evolution of computing energy efficiency: Koomey's law revisited. Cluster Comput 28, 42. https://doi.org/10.1007/s10586-024-04767-y   

Díaz, A. F., Prieto, B., Escobar, J. J., & Lampert, T. (2024). Vampire: A smart energy meter for synchronous monitoring in a distributed computer system. Journal of Parallel and Distributed Computing, 184, 104794.  https://doi.org/10.1016/j.jpdc.2023.104794 

Martínez‐Cañada, P., Perez‐Valero, E., Minguillon, J., Pelayo, F., López‐Gordo, M. A., & Morillas, C. (2023). Combining aperiodic 1/f slopes and brain simulation: An EEG/MEG proxy marker of excitation/inhibition imbalance in Alzheimer's disease. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring, 15(3), e12477. https://doi.org/10.1002/dad2.12477 

Escobar, J. J., Rodríguez, F., Prieto, B., Kimovski, D., Ortiz, A., & Damas, M. (2023). A distributed and energy-efficient KNN for EEG classification with dynamic money-saving policy in heterogeneous clusters. Computing, 105(11), 2487-2510. https://doi.org/10.1007/s00607-023-01193-7  

Conference proceedings

Sandron, A., Orozco Valero, A., García, J.M., Mancini, G., Pelayo, F., Morillas, C., Panzeri, S. & Martínez-Cañada, P. (2024, December). Evaluating Feature Importance in the Context of Simulation-Based Inference for Cortical Circuit Parameter Estimation. 17th International Conference on Brain Informatics (BI 2024). Lecture Notes in Computer Science, vol 15541. Springer, Singapore. https://doi.org/10.1007/978-981-96-3294-7_35.

Escobar, J. J., López-Rodríguez, J., García-Gil, D., Morcillo-Jiménez, R., Prieto, B., Ortiz, A., & Kimovski, D. (2024, July). Analysis of a Parallel and Distributed BPSO Algorithm for EEG Classification: Impact on Energy, Time and Accuracy. In International Work-Conference on Bioinformatics and Biomedical Engineering (pp. 77-90). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-64629-4_6   

Gómez-López, J. C., Castillo-Secilla, D., & González, J. (2024, July). Improving the Performance of EA-based Multi-population Models for Feature Selection Problems by Reducing the Individual Size in the Initial Population. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 335-338). https://doi.org/10.1145/3638530.3654424 

Díaz, A.F., Prieto, B., Escobar, J.J., Prieto, A. (2024, Junio). Sistema Inteligente de Medida de Energía para Monitorización Síncrona en Sistemas Informáticos Distribuidos. Avances en arquitectura y tecnología de computadores. Actas de las jornadas SARTECO 2024, 409–418. https://doi.org/10.5281/zenodo.11530997 

Gómez-López, J. C., Castillo-Secilla, D., González, J., Herrera, L. J., & Rojas, I. (2023, June). Towards the Identification of Multiclass Lung Cancer-Related Genes: An Evolutionary and Intelligent Procedure. In International Work-Conference on Artificial Neural Networks (pp. 553-562). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-43085-5_44 

Gómez-López, J. C., Castillo-Secilla, D., Kimovski, D., & González, J. (2023, June). Boosting NSGA-II-Based Wrappers Speedup for High-Dimensional Data: Application to EEG Classification. In International Work-Conference on Artificial Neural Networks (pp. 80-91). Cham: Springer Nature Switzerland.  https://doi.org/10.1007/978-3-031-43085-5_7  

Escobar, J. J., Rodríguez, F., Kızıltepe, R. S., Prieto, B., Kimovski, D., Ortiz, A., & Damas, M. (2023, June). Energy-Aware KNN for EEG Classification: A Case Study in Heterogeneous Platforms. In International Work-Conference on Artificial Neural Networks (pp. 505-516). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-43085-5_40 

Conference presentations

Martínez-Cañada, P. (2025, July). Inverse Modelling of Field Potentials from Simulations of Spiking Network Models: Applications in Neuroscience Research and Clinical Settings. In the workshop "Modeling Extracellular Potentials: Principles, Methods, and Applications", part of the 34th Annual Computational Neuroscience Meeting (CNS 2025).  5-9 July 2025, Florence, Italy. https://nicolomeneghetti.github.io/ECP_CNS2025_Wshop/ 

Orozco Valero, A., Gallego Molina, N. J., Luque Vilaseca, J. L., Pelayo, F., González, J., Morillas, C., Ortíz, A., Martínez-Cañada, P. (2025, March). Surrogate Modelling to Study E/I Imbalances in Children with Developmental Dyslexia. BRAININFO 2025. 9-13/3/2025 Lisbon (Portugal). https://www.thinkmind.org/library/BRAININFO/BRAININFO_2025/braininfo_2025_2_30_90046.html  

García, J. M., Orozco Valero, A., Rodríguez-González, V., Montobbio, N., Pelayo, F., Morillas, C., Poza, J., Gómez, C., Martínez-Cañada, P. (2024, October). Integrating Machine Learning and Brain Modelling to Assess Biomarkers’ Capabilities in Informing on Alterations of Cortical Circuit Parameters in Dementia. 1º Congreso de la Sociedad Española de Bioinformática y Biología Computacional (SEBiBC). 16-18/10/2024, Valencia (Spain). https://congresosebibc.com

Martínez-Cañada, P. (2024, June). Biophysically detailed cortical circuit modelling in aging research. Unite Scientific Aging Conference. 25-26/4/2024, Munich (Germany). https://aging.uniteexplores.com

Preprints

García, J. M., Orozco Valero, A., Rodríguez-González, V., Montobbio, N., Pelayo, F., Morillas, C., Poza, J., Gómez, C., Martínez-Cañada, P. (2024). A Hybrid Machine Learning and Mechanistic Modelling Approach for Probing Potential Biomarkers of Excitation/Inhibition Imbalance in Cortical Circuits in Dementia. Available at SSRN: https://ssrn.com/abstract=4977918 or http://dx.doi.org/10.2139/ssrn.4977918  

Prieto, A., Prieto, B. (2024). Five questions and answers about artificial intelligence. arXiv preprint arXiv:2409.15903. https://arxiv.org/abs/2409.15903    

Gómez-López, J. C., Castillo-Secilla, D., & Gonzalez, J. (2024). Tuning Evolutionary Multi-Population Models for High-Dimensional Problems: The Case of the Migration Process. Available at SSRN: https://ssrn.com/abstract=4846937 or http://dx.doi.org/10.2139/ssrn.4846937 

Open lectures and talks

Desarrollo y retos de la Ingeniería de Computadores" Alberto Prieto Espinosa. Conferencia pronunciada en la Facultad de Ciencias de la Universidad de Granada. Organizada por la Cátedra de IA, Ciberseguridad y Sociedad Cognitiva Telefónica-UGR. (17 de diciembre de 2024). https://hdl.handle.net/10481/98151   

"Sostenibilidad energética en Centros de Datos" Alberto Prieto Espinosa. Dyplofest 2024. Google Developers Students. ETSIIT de la Universidad de Granada. 18 de mayo de 2024. https://hdl.handle.net/10481/98281  

"Computación sostenible: estrategias para la optimización energética del procesamiento de señales y datos”. Alberto Prieto. Máster en Telemática y Redes de Telecomunicación, Universidad de Málaga.  17 de abril 2024. https://hdl.handle.net/10481/98282 

"¿Habrá suficiente energía para el desarrollo global de la inteligencia artificial?". Alberto Prieto Espinosa. Organizado por la Cátedra Mujer y Tecnología Hedy Lamarr de la Universidad de Málaga. Lugar: Escuela Técnica Superior de Ingeniería de Telecomunicación de la Universidad de Málaga, 24 de febrero 2024. https://hdl.handle.net/10481/98289 

"Green Computing: análisis de la situación y técnicas para reducción del consumo". Alberto Prieto. Máster en Ciencia de Datos e Ingeniería de Computadores, Universidad de Granada. 14 de diciembre 2023. https://hdl.handle.net/10481/98309 

"El reto de la computación verde". Alberto Prieto.  Conferencia organizada por la Academia de Ciencias Matemáticas, Físico-Químicas y Naturales de Granada, Faculta de Ciencias Universidad de Granada, 2 de noviembre 2023. https://hdl.handle.net/10481/98304 

Prieto, A., Prieto, Escobar, J.J. (2023, July). Green computing, or how to slow down the imperceptible contamination of ICTs. Invited talk in 2nd Basque Conference on Cyber Physical Systems and Artificial Intelligence, San Sebastián (Spain) July 17-21, 2023. https://doi.org/10.5281/zenodo.8152669