Welcome
CoDAlab
Control, Data and Artificial Intelligence Laboratory
An interdisciplinary research group of the Departament de Matemàtiques, Universitat Politècnica de Catalunya (UPC). We work at the intersection of applied mathematics, control theory and data science, developing methods and tools validated against real engineering and biomedical problems.
At a Glance
Institution
Universitat Politècnica
de Catalunya · UPC
Department
Departament de Matemàtiques
Group Leader
Yolanda Vidal
Status
Consolidated Group
Generalitat de Catalunya · 2009
Location
EEBE · Barcelona Est
EPSEM · Manresa
ESEIAAT · Terrassa
900+
Publications
15+
Active Researchers
2
Research Labs
About CoDAlab
CoDAlab — Control, Data and Artificial Intelligence Laboratory — is a research group of the Departament de Matemàtiques at the Universitat Politècnica de Catalunya. Recognised by the Generalitat de Catalunya as a consolidated research group since 2009, the group has sustained a long trajectory of theoretical contributions and applied projects across engineering, biomedicine and industrial systems.
Our work sits at the intersection of applied mathematics, control theory and data science. We develop methods that are mathematically rigorous and validated against experimental data from real platforms, clinical settings and industrial environments.
The group operates two fully equipped laboratories — at the EEBE campus in Barcelona and at the EPSEM campus in Manresa — and maintains active collaborations with hospitals, research centres and industry partners in Spain and internationally.
Keywords
Research Lines
CoDAlab is structured into four interdisciplinary research lines, each addressing a distinct societal challenge through artificial intelligence, data analysis and control theory.
WinTurCoM · Wind Turbine Condition Monitoring
AI-based frameworks for resilient wind energy infrastructures. Condition monitoring and structural health monitoring of offshore wind turbines.
Explore →Structural Health Monitoring · SHM — Data-Driven Damage Detection & Prognosis
Data-driven and AI-based methodologies for detecting, localising and assessing structural damage in engineering systems.
Explore →Control Systems · Modelling, Feedback Design & Cyber-Physical Systems
Feedback systems for stability and robustness: sliding mode, model predictive control, H∞/LMI and Lyapunov-based design.
Explore →CellsiLab · Computational Hematopathology & Biomedical AI
Deep learning for automatic recognition of blood cells and automated diagnosis of haematological diseases. In collaboration with Hospital Clínic de Barcelona.
Explore →Selected Projects
SNAPSHOT — AI-Based Monitoring of Composite Manufacturing and Structural Health
AI-driven system for continuous monitoring of the manufacturing process and structural health of composite materials, aimed at early detection of damage and improved safety and sustainability.
Funded by · Agencia Estatal de Investigación (PID2024-160220OB-C22) · 2025–2028
xAI-HEALTH — Explainable Deep Learning for Medical Image Analysis
Development and clinical evaluation of explainable AI methods for medical image analysis, to increase the reliability and clinical trust of deep learning techniques in healthcare settings.
Funded by · Agencia Estatal de Investigación (PID2023-146261OB-I00) · 2024–2027
AIWinTurCoM — Deep Learning for Predictive Maintenance of Wind Turbines
Development and validation of deep learning and machine learning strategies for predictive maintenance and early detection of structural damage in wind turbines.
Funded by · Agencia Estatal de Investigación (PID2021-122132OB-C21) · 2022–2027
Haematological Image Classification
Deep learning methods for the automatic classification of peripheral blood cell images, developed in collaboration with IDIBAPS and Hospital Clínic de Barcelona to support clinical diagnosis of haematological disorders.
Collaboration · IDIBAPS · Hospital Clínic de Barcelona
FloWinTurCoM — Floating Wind Turbine Control and Monitoring
Intelligent monitoring, pitch control and structural damping for floating offshore wind turbines. Addresses the combined challenges of wave-induced loads, drivetrain faults and blade pitch actuator failures.
Funded by · Ministerio de Economía y Competitividad · 2018–2021
Rate-Dependent Hysteresis — Modelling, Analysis and Identification
Mathematical modelling and parameter identification of hysteretic behaviour in magnetorheological dampers, with applications to semi-active structural control.
Funded by · Ministerio de Economía y Competitividad · 2017–2020
CEOR Technology with Chemically Enhanced Gas Recovery
Control and data analysis methods applied to enhanced oil recovery processes, with modelling and experimental validation in collaboration with Colombian institutions.
Funded by · COLCIENCIAS, Colombia · 2017–2019
Laboratory Infrastructure
EEBE Lab
Escola d'Enginyeria de Barcelona Est · Campus Besòs
Equipment
EPSEM Lab
Escola Politècnica Superior d'Enginyeria de Manresa
Equipment
LabTECH
Escola Superior d'Enginyeries Industrials, Aeroespacials i Audiovisuals · Terrassa
Focus
Equipment
External Partners
Research collaborations and institutional links
Collaboration & Opportunities
CoDAlab welcomes inquiries from prospective doctoral students, postdoctoral researchers and institutions interested in joint research projects or knowledge transfer initiatives.
We participate in competitive national and international projects, maintain active connections with hospitals and industry, and regularly host researchers from partner universities in Spain and abroad.
If you are interested in collaborating, pursuing a PhD within the group, or exploring applied research partnerships, we encourage you to reach out directly to the group.
PhD Positions
Doctoral research in AI, control and applied mathematics within an international environment.
Postdoctoral Research
Opportunities for experienced researchers to join active projects and develop independent lines.
Industry & Institutions
Joint projects, technology transfer and applied research agreements welcome.
Contact
Get in touch with CoDAlab
For research inquiries, collaboration proposals or information about the group's activities, visit our website or contact us directly.
Address
Departament de Matemàtiques
Universitat Politècnica de Catalunya
Campus Besòs – EEBE
Av. Eduard Maristany, 16
08019 Barcelona, Spain
CoDAlab · Control, Data and Artificial Intelligence Laboratory · Departament de Matemàtiques · Universitat Politècnica de Catalunya (UPC)
Consolidated Research Group · Generalitat de Catalunya
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