• Error assessment and adaptivity. Development, analysis and implementation of numerical tools for assessing the error in solutions produced by Finite Element and Reduced Order Models. Mesh and model adaptivity to monitor the numerical accuracy. PI: P. Díez.

  • Data-driven Geophysical Modeling. High-fidelity models of large-scale geophysical phenomena in the earth crust. Data assimilation and model updating. Bayesian approaches to inverse problems. PI: S. Zlotnik.

  • Data-driven Biomechanical Modeling. Modeling and simulation of biomechanical devices and bio-systems. Computational design of metamaterials for health care applications. PI: A. García-González.

  • Reduced Order Models and Surrogate Models. Intrusive and nonintrusive Reduced Order Models, using different numerical strategies accompanied by error control. Special insight in Proper Generalized Decomposition (PGD) and Proper Orthogonal Decomposition (POD). PI: P. Díez.