Experts in:

Modeling and simulation

  • Acoustic or vibroacoustic.
  • Multiphysics phenomena.
  • Manufacturing processes: injection, stamping, forging, additive manufacturing, etc.
  • Processes in the entity or company through event- or agent-based simulation.

Statistics and Big Data

  • Statistical advice and data analysis.
  • Time series forecasting.
  • Elaboration of maps from spatial data.
  • Design of experiments, clinical trials.
  • Biostatistics, epidemiology.
  • Applications in the field of health.


  • Process optimisation.
  • Stock optimisation.
  • Resource optimisation.
  • Resource location optimisation.
  • Transport route planning.
  • Work planning.
  • Optimal decision support.
  • Optimisation of industrial and business processes.

Artificial intelligence

  • Automatic learning.
  • Neural networks.
  • Deep learning.
  • Machine learning.
  • Bayesian Networks.
  • Development of digital twins.


  • Programming in scientific languages: Fortran, C, C++, Python, Matlab, R.
  • Development of graphical interfaces.
  • Implementation of commercial and free software packages.
  • Data modelling / Databases.
  • Use of free software packages.
  • Use of commercial software packages.
  • Development of software packages.
  • WEB applications / technologies.

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 the flow of users by services.
  • Optimisation of the planning of the location of primary health care facilities in uncertain environments of the evolution of demographic rates over a time horizon.
  • Optimisation of the planning of the provision of health equipment in uncertain environments of the evolution of demographic rates and types and intensity of diseases and epidemics over a time horizon.
  • Optimisation of ambulance fleet types: Sizing and location in an uncertain environment of service demand.
  • Optimisation 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.

Challenge 5: Environment

  • Optimisation of resource use planning in emergencies.

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