ICREA Academia

Santiago Badia

ICREA Academia 2014

Universitat Politècnica de Catalunya (UPC) · Engineering Sciences

Santiago Badia (Palma, 1978) is Full Professor of Computational Science and Engineering at UPC and leader of the “Large Scale Scientific Computing” Department at CIMNE. Since 2006, he has published 56 articles, 5 book chapters, and a monograph. He has been semi-plenary lecturer at the WCCM, and plenary lecturer at Coupled'15, HPCSE 2015, and YIC17. Prof. Badia has received the 2006 SEMNI and ECCOMAS awards for the best national and European thesis in computational mechanics, Outstanding PhD award at UPC 2005-2006, 2010 Juan Carlos Simo young researcher award in computational mechanics, 2012 Young Investigator Award in Applied Mathematics from the Spanish Society of Applied Mathematics, the 2016 Young Investigator award from the Royal Academy of Engineering of Spain, and Ramon y Cajal, Marie Curie, and UT Austin JT Oden fellowships. He obtained one Starting Grant and two Proof of Concept Grants from the European Research Council.

Research interests

His research focuses on the development, mathematical analysis, and application of numerical methods in engineering and sciences, and high performance scientific computing. He actively works on advanced discretization techniques, mainly finite elements, for the numerical approximation of complex multiphysics phenomena governed by partial differential equations, e.g., additive manufacturing and fusion reactor simulations. His research is also focused on massively parallel and optimal linear solvers for the (non)linear systems resulting from discretization. He is a main developer of FEMPAR, his team’s in-house code, a massively parallel finite element software distributed as free software that has been positioned as world’s most scalable domain decomposition solver, and has efficiently run at the whole JUQUEEN supercomputer (the largest supercomputer in Europe) on 458,672 processors. FEMPAR is now on the High-Q club of the most scalable European scientific computing codes.


Finite element methods, numerical analysis, large scale computing, domain decomposition, multi-physics simulations