Results

Research articles

Cárdenas Sánchez, M., Orozco Valero, A., García, J.M., ... & Martínez-Cañada, P. (2026). A Framework Integrating Spiking Cortical Circuit Modeling and Simulation-Based Inference to Probe Biomarkers of Cortical Dysfunction in Alzheimer's Disease. Interdiscip Sci Comput Life Sci (2026). https://doi.org/10.1007/s12539-026-00817-8 

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  

Ortega, A., Cano-Delgado, A. M., Prieto, B., & González, J. (2023). Design of a standard and programmatically accessible interface for smart meters to allow monitoring automation of the energy consumed by the execution of computer software. Sustainability, 15(3), 1900.  https://doi.org/10.3390/su15031900   

Conference proceedings

Escobar, J. J., Aquino-Brítez, D. A., Prieto, B., Martinez, R. J., Ortiz, G. M., & Ortiz, A. (2026). Balancing Accuracy and Energy Efficiency in EEG Classification: An Evaluation of Wrapper-Based Approaches. In Bioinformatics and Biomedical Engineering, 12th International Conference, IWBBIO 2025. Lecture Notes in Computer Science, vol 16050 (pp. 253-266). Springer. https://doi.org/10.1007/978-3-032-08455-2_19 

Ortiz, A., Gallego-Molina, N.J., Rodríguez-Rodríguez, I., Peinado, A., Gil-montoya, M.D., Martínez-Cañada, P., Morillas, C. (2025, June). Exploring Brain Lateralization Using Tensor Decomposition of EEG Phase-Amplitude Coupling. 18th International Work-Conference on Artificial Neural Networks (IWANN 2025), A Coruña (Spain), 16-18 June, 2025.  Lecture Notes in Computer Science, vol 16009. Springer, Cham. https://doi.org/10.1007/978-3-032-02728-3_2  

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  

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, June). 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 

Ortega, A., Vázquez, V., Megías, C., González, J., Rodríguez-Álvarez, M., Díaz, J., & Ros, E. (2024, October). Time Transfer and Clock Synchronization Analysis over Spine-Leaf Networks. In 2024 IEEE International Symposium on Precision Clock Synchronization for Measurement, Control, and Communication (ISPCS) (pp. 1-6). IEEE. https://doi.org/10.1109/ISPCS63021.2024.10747714 

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

Cárdenas Sánchez, M., Rodríguez-González, V., Pelayo, F., Morillas, C., Hoshi, H., Hirata, Y., Shigihara, Y., Poza, J., Gómez, C., & Martínez-Cañada, P. (2026, July). Characterizing Aperiodic and Periodic MEG Activity in Mixed Dementia. Poster PS05-09AM-096, 15th FENS Forum of Neuroscience, Barcelona, Spain, 6–10 July 2026. https://fens2026.abstractserver.com/program/#/details/presentations/3945 

Martínez-Cañada, P. (2026, June). From Circuits to Signals and Back: Integrating Biophysical Forward Modelling and Simulation-Based Inference to Decode Brain Dynamics. Keynote K-1, NEST Conference 2026, virtual, 16-17 June 2026. 16 June 2026, 9:15, Zoom. https://ebrains.eu/news-and-events/events/2026/nest-conference-2026 

Martínez-Cañada, P., Orozco Valero, A., Cárdenas Sánchez, M., Rodríguez-González, V., Montobbio, N., Pelayo, F., Morillas, C., Poza, J., Gómez, C. (2025, October). Circuit-level biomarker discovery in Alzheimer’s Disease through inverse modelling of mechanistic neural circuits. 38th ECNP Congress. https://www.ecnp.eu/congress2025/ 

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/ 

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

Neurophysiological excitation/inhibition imbalance in young adults burdened with childhood interpersonal trauma. Alejandro Orozco Valero, Natalia Kopiś-Posiej, Víctor Rodríguez-González, Víctor Gutiérrez-de Pablo, Christian Morillas, Jesús Poza, Carlos Gómez, Pablo Martínez-Cañada, Paweł Krukow. bioRxiv 2026.01.14.699432; doi: https://doi.org/10.64898/2026.01.14.699432 

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 

PhD theses

Title: Energy-aware Efficient Multi-population Models for High-dimensional Feature Selection Biomedical Problems
PhD candidate: Juan Carlos Gómez López
Supervisors: Jesús González Peñalver and Daniel Castillo Secilla
Institution: University of Granada
Grade: Outstanding, cum laude
Date: 24 July 2025
Type: International Doctorate