Summer School · 19th edition
19th Machine Learning & Advanced Statistics Summer School
An intensive programme of 12 courses (15 hours each) across two weeks, covering the theoretical foundations and practical applications of the machine-learning and modern statistical techniques most widely used today. Madrid · June 14–25, 2027.
What we work on
Research lines
Four core research areas — from probabilistic graphical models to computational neuroscience — bridging theory and real-world application.
Probabilistic Graphical Models
Bayesian networks, multidimensional classifiers, clustering and feature selection.
Learn more →Machine Learning in Industry 4.0
Predictive maintenance, industrial cybersecurity, anomaly detection and real-time process analytics.
Learn more →Heuristic Optimization
Evolutionary algorithms and estimation-of-distribution algorithms for problems of high computational complexity.
Learn more →Computational Neuroscience
Neuronal morphology. Parkinson’s and Alzheimer’s biomarkers. Cajal Blue Brain with the CTB-UPM.
Learn more →Research Projects
JRC Articles
Awards
Theses
Leading Innovation in Computational Intelligence
The Computational Intelligence Group (CIG) was created in 2008 and is led by professors Pedro Larrañaga and Concha Bielza. Research of CIG members, both theoretical and practical, is devoted to modelization (from a statistical and machine learning perspectives), heuristic optimization, and neuroinformatics. The CIG has been involved in more than 160 research projects, mostly in public competitive calls but also for private companies. Current public projects include several national projects from the Spanish Ministry of Science and Innovation. CIG has collaborated with companies as Abbott, Aingura IIoT, Arthur Andersen, Atos Origin, Bank of Santander, Etxe-Tar, Fundación BBVA, Fundación Gil Gayarre, Gaindu, Iberdrola, Idealista, Olocip 11, Panda Security, Progenika Biopharma, Repsol, Telefónica I+D and Titanium Industrial Security.
A leaflet about the Computational Intelligence Group is available here.
The Group
Collaborations: Public Contracts
Collaborations: Private Contracts
Collaborations: Academia
Highlighted Books
Data-driven Computational Neuroscience
Bielza, C., & Larrañaga, P. (2021). Data-driven Computational Neuroscience: Machine Learning and Statistical Models. Cambridge University Press.
Industrial Applications of Machine Learning
Larrañaga, P., Atienza, D., Diaz-Rozo, J., Ogbechie, A., Puerto-Santana, C., & Bielza, C. (2018). Industrial Applications of Machine Learning. CRC Press.
机器学习的工业应用
Larrañaga, P., Atienza, D., Diaz-Rozo, J., Ogbechie, A., Puerto-Santana, C., & Bielza, C. (2023). 机器学习的工业应用. CRC出版社.