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.


  • 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.


  • 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:


Contact us

Tell us your projects or needs and we will look for ways to collaborate

Free consultation
(+34) 881 813 373