BCAM
Academic
Experts in:
Modeling and simulation
- Manufacturing processes: injection, stamping, forging, additive manufacturing, etc.
- Fluids: gases, liquids.
- Fluid-structure interaction.
- Mechanical or structural.
- Combustion.
- Environmental.
- Multiphysical phenomena.
Statistics and Big Data
- Statistical advice and data analysis.
- Time series forecasting.
- Production of maps from spatial data.
- Environmental and energy statistics.
- Biostatistics, epidemiology.
- Applications in the field of health.
- Statistical applications for industry or public administrations.
Optimization
- Resource optimisation.
- Resource location optimisation.
- Planning of transport routes.
- Optimal decision support.
- Optimisation of industrial and business processes.
Artificial intelligence
- Automatic learning.
- Neural networks.
- Bayesian networks.
- Deep learning.
- Machine learning.
- Hybrid models based on data and physics.
Computing
- Programming in scientific languages: Fortran, C, C++, Pyton, Matlab, R.
- Development of software packages.
- Parallelisation of algorithms.
- Use of free software packages.
- Programming on GPUs.
- Distributed computing.
- High performance computing.
- Data/database modelling
- Quantum computing.
Areas of experience:
Challenge 1: Health
- Visualisation, processing and analysis of medical images. Characterisation of false positives. Learning models using large databases (machine/deep learning).
- Evolution of demographic rates. Population projections and generation of scenario trees over a time horizon.
- Characterisation of population habits. Simulation of user flow by services.
- Optimization of the planning of the location of primary health centres in uncertain environments of the evolution of demographic rates over a time horizon.
- Optimization of ambulance fleet types: Sizing and location in an uncertain environment of service demand.
- Optimization of the distribution of health resources, both human and material, in emergency situations.
Challenge 3: Energy
- Forecasting and planning of energy production for domestic or industrial use.
- Optimization of energy distribution networks.
- Optimization of the location of renewable sources (wind, solar, photovoltaic, etc.).
- Optimization of maintenance planning for electricity generators.
- Numerical simulation of heat transfer and combustion processes.
- Decision-making assistance in energy processes.
Challenge 5: Environment
- Simulation, prediction and control of pollutant emissions.
- Modelling and simulation of forest fires.
- Optimization of sustainable forest exploitation planning.
- Optimization of irrigation planning for agricultural and livestock purposes.
- Optimization of the sustainable planning of the exploitation of hydrographic basins for industrial purposes.
Success stories:
Multiscale Simulations to Develop Advanced Battery Materials
Neiker: Mapping High-Resolution Soil Properties With Geoadditive Models
Machine Learning to improve customer satisfaction in insurance
More success stories:
http://www.bcamath.org/documentos_public/archivos/BCAM_Industry.pdf
