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
900+
Publications
15+
Active Researchers
8
Research Lines
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
Eight active areas combining mathematical foundations with engineering applications.
Artificial Intelligence
Machine learning and deep learning for classification, pattern recognition and automated inference in engineering and clinical data.
Data Analysis
Statistical and data-driven methods for knowledge extraction from experimental and operational signals in industrial and biomedical systems.
Control Systems
Robust and nonlinear control: H∞, LMI and Lyapunov-based design for uncertain, large-scale and decentralised systems.
Structural Health Monitoring
Damage identification and fault detection in civil and mechanical structures from experimental measurements and operational data.
Biomedical Applications
Automatic classification of blood cell digital images for haematological disease diagnosis. Collaboration with IDIBAPS and Hospital Clínic de Barcelona.
Industrial Systems
Data-driven fault diagnosis and intelligent condition monitoring of wind turbines, with emphasis on floating offshore platforms.
Dynamic Systems
Mathematical analysis of nonlinear dynamics: bifurcations, periodic orbits, global asymptotic stability and integrability.
Water Channel Control
Automatic operation of irrigation canals and water distribution networks for improved hydraulic resource management.
Selected Projects
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
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
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
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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