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# Computational Intelligence Group

## Posts

- [Blog](https://cig.fi.upm.es/blog/)

## Pages

- [Home](https://cig.fi.upm.es/) - The Computational Intelligence Group (CIG) is lead by Pedro Larrañaga and Concha Bielza. Our research is devoted to modelization, heuristic optimization and neuroinformatics.
- [Proceedings](https://cig.fi.upm.es/proceedings/) - 2026 E. Valero-Leal, B. Bischl, P. Larrañaga, C. Bielza, G. Casalicchio (2026). Optimal Transport Group Counterfactual Explanations. Proceedings of the 43rd International Conference on Machine Learning, ICML 2026. ADR-EDA: A Reliability-Aware controller for dynamic multiobjective estimation of distribution algorithms. XXI Edición de la Conferencia de la Asociación Española para la Inteligencia Artificial, CAEPIA 2026. 2025
- [Presentations](https://cig.fi.upm.es/presentations/) - Pedro Larrañaga (2025) Inteligencia Artificial Interpretable con Redes Bayesianas. Keynote talk at XI Reunion Nacional de la Academia Mexicana de Computación AMEXCOMP2025, Universidad Nacional Autónoma de México, México DF, October 23, 2025. Pedro Larrañaga (2025) Estimation of Distribution Algorithms in Statistics and Machine Learning. Keynote talk at XI Reunion Nacional de la Academia Mexicana de
- [JCR Articles](https://cig.fi.upm.es/jcr-articles/) - 2026 Alejandre V, Bielza C, Larrañaga P (2026). Bandwidth selectors on semiparametric Bayesian networks. Information Sciences, 740 (2026) 123198. Sojo R, Larrañaga P, Bielza C (2026). Transfer learning for nonparametric Bayesian networks. Knowledge-Based Systems, 344 (2026) 116077. 2025 Lozano-Paredes D, Bote-Curiel L, Sabater-Molina M, Bielza C, Gimeno-Blanes JR, Muñoz-Romero S, Gimeno-Blanes FJ, Larrañaga P, Rojo-Álvarez
- [18th Machine Learning and Advanced Statistics Summer School](https://cig.fi.upm.es/mlas/) - The MLAS (formerly ASDM) is an intensive set of courses providing attendees with an introduction to the theoretical foundations as well as the practical applications of some of the machine learning methods and the modern statistical analysis techniques currently in use.
- [MSc Theses](https://cig.fi.upm.es/msc-theses/) - 2025 Arteaga J (2025). Algoritmos de Estimaciones de Distribuciones Aplicados al Algoritmo Iterative Proportional (supervised by C. Bielza and P. Larrañaga). Boukaich I (2025). Clasificación supervisada aplicada a la identificación de los ascensores del Aeropuerto de Bilbao (supervised by C. Bielza and P. Larrañaga). Cantarero JL (2025). Descubrimiento Causal para Análisis de Anomalías en Mantenimiento
- [Awards](https://cig.fi.upm.es/awards/) - Personal Premio de Consolidación de la Actividad Investigadora desarrollada en la UPM Pedro Larrañaga, 2026 National Award of Statistics Concha Bielza, 2024 ELLIS Fellow Pedro Larrañaga , 2023 ELLIS Fellow Concha Bielza, 2023 Fellow of the Asia-Pacific Artificial Intelligence Association Concha Bielza, 2024 Fellow of the Asia-Pacific Artificial Intelligence Association Pedro Larrañaga, 2021 IEEE Fellow, Pedro Larrañaga,
- [People](https://cig.fi.upm.es/people/) - The CIG members are experts in computer science, driving research and education in artificial intelligence, data sciences, bayesian network, machine learning,
- [Patents](https://cig.fi.upm.es/patents/) - 2025 Díaz-Rozo J, Puerto-Santana C, Ocampo-Martínez C, Bielza C, Larrañaga P, A computer implemented method and system for health monitoring of structures. 18-09-2025, 2025. (Worldwide applications) 2013 García-Escudero R, Paramio JM, Larrañaga P, Bielza C, Test Predictor de Supervivencia Global de Adenocarcinoma de Pulmón, Granting date: 26-4-2013, 2013. (Worldwide applications) 2010 García A, Suárez B, Betanzos M, López Vivanco GM, Armañanzas
- [ESTIMATION OF DISTRIBUTION ALGORITHMS](https://cig.fi.upm.es/estimation-of-distribution-algorithms/) - Abstract In this chapter, estimation of distribution algorithms will be described. These algorithms belong to the evolutionary computation field and are characterized by evolving a population of candidate individuals as solutions of the optimization problem estimating at each generation the joint probability distribution of the selected individuals and then sampling new individuals from that distribution.
- [Technical Reports](https://cig.fi.upm.es/technical-reports/) - arXiv E Valero-Leal , P Larrañaga, C Bielza. (2025). Actionable Counterfactual Explanations Using Bayesian Networks and Path Planning with Applications to Environmental Quality Improvement. arXiv:2508.02634 R Sojo, J Díaz-Rozo, C Bielza, P Larrañaga. (2025). Binned Semiparametric Bayesian Networks. arXiv:2506.21997 V Alejandre, C Bielza, P Larrañaga. (2025). Bandwidth Selectors on Semiparametric Bayesian Networks. arXiv:2506.16844 C Puerto-Santana,
- [Books](https://cig.fi.upm.es/books/) - Books Bielza, C., & Larrañaga, P. (2021). "Data-Driven Computational Neuroscience. Machine Learning and Statistical Models". Cambridge University Press. Larrañaga, P., Atienza, D., Díaz-Rozo, J., Ogbechie, A., Puerto-Santana, C., & Bielza, C. (2019). "Industrial Applications of Machine Learning". CRC Press. Bielza, C., Salmerón, A., Alonso-Betanzos, A., Hidalgo, J. I., Martínez, L., Troncoso, A., Corchado, E., & Corchado, J. M. (2013). "Advances in Artificial Intelligence, Lecture Notes in Artificial Intelligence,
- [PhD Theses](https://cig.fi.upm.es/phd-theses/) - 2025 Soloviev V (2025). New advances in estimation of distribution algorithms for quantum machine learning and industrial scenarios (supervised by C. Bielza and P. Larrañaga). 2024 Villa Blanco C (2024). Feature subset selection and multi-dimensional continuous-time Bayesian network classifiers for streaming data (supervised by C. Bielza and P. Larrañaga). 2023 Quesada D (2023). Multivariate time-series modelling
- [Contact](https://cig.fi.upm.es/contact/) - Social Media:
- [Projects](https://cig.fi.upm.es/projects/) - IDEA-CM: Inteligencia artificial para la industria 4.0: generación de datos, modelado avanzado, optimización e interpretabilidad Duration: 2025-2028 Funding: Comunidad de Madrid (public). INDUSTR-IA: New Solutions Based on Artificial Intelligence for Industrial Production Efficiency and Flexibility Duration: 2024-2027 Funding: Ministerio de Ciencia, Innovación y Universidades (public), Agencia Estatal de Investigación (public). Specific Collaboration Agreement Number 7:
- [Research Areas](https://cig.fi.upm.es/research/) - Data Science Leader: Concha Bielza In this area a data set is analysed with statistical and machine learning techniques to extract useful information to be applied in different domains. Current issues of interest include: data streams, multi-dimensional supervised classification, multi-label classification, clustering in high-dimensional spaces, data imputation, feature subset selection using methods as Bayesian networks, regularization, classification by
- [Media](https://cig.fi.upm.es/media/) - CIG's Pedro Larrañaga talked for "Real Academia de Ciencias Exactas, Físicas y Naturales de España" about Explainable AI (XIA) here (in Spanish). (June 2024) CIG's Pedro Larrañaga and Concha Bielza talked about Machine Learning and its application in the Coronavirus crisis here. (December 2020) CIG's Pedro Larrañaga talks about how Artificial Intelligence can be applied to
- [Software](https://cig.fi.upm.es/software/) - 3DSOMAMS The definition of the soma is fuzzy, as there is no clear line demarcating the soma of the labeled neurons and the origin of the dendrites and axon. Thus, the morphometric analysis of the neuronal soma is highly subjective. This software provides a mathematical definition and an automatic segmentation method to delimit the neuronal
- [IA CONECTA 2024-ELLIS Unit Madrid](https://cig.fi.upm.es/iaconecta/) - EVENTO IA CONECTA 2024 - ELLIS Unit Madrid. Madrid, Círculo de Bellas Artes de Madrid, 11 de diciembre 2024, 09:30 a 16:30 H. La Unidad ELLIS Madrid es parte de una red europea de excelencia en Inteligencia Artificial (IA) y aprendizaje automático, busca promover la colaboración en investigación avanzada entre diferentes disciplinas, academia y empresas.
- [3DSomaMS](https://cig.fi.upm.es/3dsomams/) - Installation This software has been developed as an R package so is needed an R environment. R can be downloaded from http://cran.rstudio.com/index.html. It must be installed for 64-bit OS. To process the meshes our package uses MeshLab. The latest version of MeshLab is only available for Microsoft Window 64-bits, therefore this package only runs in this

## Teams

- [Concha Bielza](https://cig.fi.upm.es/cigmembers/concha_bielza/) - Concha Bielza received the M.S. degree in Mathematics from Universidad Complutense de Madrid, Madrid, Spain, in 1989 and the Ph.D. degree in Computer Science from Universidad Politécnica de Madrid, Madrid, in 1996 (extraordinary doctorate award). She is currently (since 2010) a Full Professor of Statistics and Operations Research with the Departamento de Inteligencia Artificial, Universidad
- [Pedro Larrañaga](https://cig.fi.upm.es/cigmembers/pedro-larranaga/) - Pedro Larrañaga is Full Professor in Computer Science and Artificial Intelligence at the Technical University of Madrid (UPM) since 2007. He received the MSc degree in mathematics (statistics) from the University of Valladolid and the PhD degree in computer science from the University of the Basque Country (“excellence award”). Before moving to UPM, his academic
- [Yumeng Shi](https://cig.fi.upm.es/cigmembers/yumeng-shi/) - Yumeng Shi Ph.D. Student in Artificial Intelligence, Universidad Politécnica de Madrid Computational Intelligence Group (CIG) Education • Ph.D. in Artificial Intelligence, Universidad Politécnica de Madrid (UPM), 2025–Present China Scholarship Council (CSC) • M.Sc., Northwestern Polytechnical University (NWPU), 2022–2025 Recommended for admission without examination • B.Sc., Northeast Forestry University (NEFU), 2018–2022 National Scholarship recipient; Merit Student;
- [Juan Fernández Del Pozo](https://cig.fi.upm.es/cigmembers/juan-fernandez-del-pozo/) - Juan Fernández del Pozo Romero is a PhD student in Artificial Intelligence at Universidad Politécnica de Madrid, currently working with the Computational Intelligence Group (CIG). His research focuses on interpretable structure learning of Bayesian Networks, particularly in the context of explainable AI (XAI) and its applications in machine learning and optimization. He previously worked as
- [José M. De Miguel](https://cig.fi.upm.es/cigmembers/jose-m-de-miguel/) - José M. De Miguel is finishing a BSc in Mathematics and Computer Science at the Technical University of Madrid, where he ranks among the university’s top 5% students. In September 2025, he will begin an MRes in Artificial Intelligence. Alongside his studies, he works as an undergraduate research assistant in the Computational Intelligence Group, designing incremental
- [Bojan Mihaljevic](https://cig.fi.upm.es/cigmembers/bojan-mihaljevic/) - Assistant Professor at the Department of Artificial Intelligence at the Universidad Politécnica de Madrid. My research is focused on graphical models, and in particular in Bayesian networks, as well as applied machine learning, especially in neuroscience. First author of nine papers in top journals, with an h-index of 8 and over 210 citations. Have given
- [Kevin Paniagua](https://cig.fi.upm.es/cigmembers/kevin-paniagua-romero/) - Kevin Paniagua Romero, a Spanish-Bolivian tech enthusiast, is currently pursuing a Degree in Computer Engineering at Universidad Politécnica de Madrid (UPM). His academic journey has been marked by rigorous studies and practical experiences, shaping him into a proficient professional in the field of IT. Kevin's educational background includes a Higher Technician in Development of Web
- [Rafael Sojo](https://cig.fi.upm.es/cigmembers/rafael-sojo/) - Master's in Data Science award to second best Master's Final Project during the academic course 2022-2023: Improving Machine Learning-based Bridge Health Monitoring Systems Scalability with Transfer Learning Download Full CV
- [Juan Antonio Fernández](https://cig.fi.upm.es/cigmembers/juan-antonio-fernandez/) - Dr. Juan Antonio Fernandez del Pozo is currently Associate Professor of Statistics and Operations Research at School of Computer Science and member of the Computational Intelligence Group at the UPM. He has published more than 60 articles, books chapters and confenrence comunications. He has participated in more than 30 research national and international proyects. He
- [Carlos Li Hu](https://cig.fi.upm.es/cigmembers/carlos-li-hu/) - Carlos Li Hu received the Double B.S. degree in Computer Science and Mathematics from the Universidad Autónoma de Madrid (UAM) in 2019. After working as a Big Data Analyst at Minsait (an Indra company), he chose to follow a more technical career. Therefore, he obtained the M.S. in Artificial Intelligence at the Universidad Politécnica de
- [Jorge Casajús](https://cig.fi.upm.es/cigmembers/jorge-casajus/) - After his graduation as a physicist by the Autonomous University of Madrid (UAM) in 2021, Jorge decided to switch career path and seek a more mathematical and data-oriented approach. As such, he got enrolled in the Artificial Intelligence MSc at the Technical University of Madrid (UPM). Here, he was granted the José Cuena award for
- [Victor Alejandre](https://cig.fi.upm.es/cigmembers/victor-alejandre/) - Victor Alejandre studied his B.Sc in Mathematics at the Universidad Autónoma de Madrid (2017- 2021) where he specialized in the areas of Statistics and Analysis. Subsequently, he obtained a M.Sc. degree in Artificial Intelligence at Universidad Politécnica de Madrid (2022-2023), where he is currently a Ph.D. student at the Artificial Intelligence Department. Research Interests: His
- [Laura Gonzalez](https://cig.fi.upm.es/cigmembers/laura-gonzalez/) - Laura received her B.Sc in Information Science at the Complutense University of Madrid. She has worked as a marketing and communication officer during her professional career in some areas, mainly Technology. Laura worked at Hyperion Solutions Iberica-Oracle (Business Intelligence) and Stryker (Medical Technology). She also worked at the research centers of Politecnica University of Madrid,
- [Enrique Valero](https://cig.fi.upm.es/cigmembers/enrique-valero/) - Enrique Valero-Leal first studied in the University of Murcia, where he got his B.Sc. in Computer Science and he then moved to Universidad Politécnica de Madrid, where he currently pursues a PhD in Artificial Intelligence Since then, he has been participating in miscellaneous research projects, both from public funding (BAYESTREAMS) and private funding (BBVA foundation