Joint Projects
IN-DEEP
UPV/EHU, BCAM, and Tecnalia participate in IN-DEEP (Real-time inversion using self-explainable deep learning driven by expert knowledge) Doctoral Network, funded by the European Union (HORIZON-MSCA-2022-DN-01-01, 2024-2027) and coordinated by David Pardo from UPV/EHU. Javier Del Ser coordinates the Tecnalia team and contribution to IN-DEEP, and Judit Muñoz-Matute coordinates the IN-DEEP BCAM team. For more information, see link-to-come.
- Application Areas: Industry, Energy, Health
- Research Areas: Physics-Aware Neural Networks, Trustworthy AI, XAI, Bias & Ethics
IA4TES
BCAM and Tecnalia participate in IA4TES (Artificial Intelligence for a Sustainable Energy Transition), funded by the Ministry of Economic Affairs and Digital Transformation (AI R&D Missions 2021, 21st Century Energy, 2022-2024). Vincenzo Nava and Santiago Mazuelas coordinate the BCAM node of IA4TES. For more information, see link.
- Application Areas: Industry, Energy
- Research Areas: Physics-Informed Neural Networks, Open-set recognition & Lifelong Learning
BEREZIA
Tecnalia and BCAM participate in BEREZIA (Towards a Continuous, Autonomous, Sustainable and Self-Explanatory Artificial Intelligence) funded by the Basque Government, ELKARTEK, 2023 - 2024. BEREZIA is coordinated by Javier Del Ser at Tecnalia.
- Application Areas: Industry
- Research Areas: Open-world learning, AutoML & Metalearning, Stream Learning & Concept Drift
MATHEOLO
BCAM and Tecnalia participate in MATHEOLO (Advanced Numerical Methods and Neural Networks for Structural Health Monitoring of Offshore Wind Platforms) funded by the Spanish Ministry of Economy and Competitiveness (TED2021-132783B-I00, 2022-2024). David Pardo and Vincenzo Nava coordinate the two groups respectively. For more information, see link.
- Application Areas: Industry, Energy
- Research Areas: Physics-Informed Neural Networks
