Projects per year
Personal profile
Biography
Santiago Badia is Professor of Computational Mathematics at Monash since June 2019. He obtained his PhD at Universitat Politècnica de Catalunya (UPC) in 2006. Previously, he worked at the Applied Mathematics departments at Politecnico di Milano (Italy) in 2006 and Sandia National Labs (New Mexico, USA) in 2007-08. He joined UPC in 2009, where he was appointed Professor of Computational Science and Engineering in 2017. He is adjoint researcher at CIMNE (Barcelona), where he leads the Large Scale Scientific Computing Department.
He works on the numerical approximation of partial differential equations (PDEs), e.g., using finite element methods, for modelling fluid and solid mechanics, electromagnetics, and multiphysics problems. He is particularly interested in large scale scientific computing and numerical linear algebra.
As a by-product of his research, Prof Badia leads some high-performance scientific projects, like FEMPAR. FEMPAR provides state-of-the-art numerical discretizations of PDEs and highly scalable numerical linear algebra solvers. FEMPAR has been used to model metal additive manufacturing, superconductor devices, breeding blankets in fusion reactors, or nuclear waste repositories. It has attained perfect weak scalability up to 458,672 cores in JUQUEEN (Germany) solving up to 60 billion unknowns. In 2019 he initiated the Gridap project, which heavily relies on functional programming and multiple dispatching in Julia, with the aim to create an easy-to-use but very efficient PDE solver.
Students interested in fully-funded PhD projects can find more information here.
Research area keywords
- Computational Science and Engineering
- Numerical Analysis
- Numerical Linear Algebra
- Partial Differential Equations
- Parallel Computing
Network
Projects
- 1 Active
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Interface-aware numerical methods for stochastic inverse problems
Droniou, J., Cui, T., Badia, S., Marzouk, Y. & Carrera, J.
8/09/21 → 8/09/24
Project: Research
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A robust and scalable unfitted adaptive finite element framework for nonlinear solid mechanics
Badia, S., Caicedo, M. A., Martín, A. F. & Principe, J., 1 Dec 2021, In: Computer Methods in Applied Mechanics and Engineering. 386, 23 p., 114093.Research output: Contribution to journal › Article › Research › peer-review
1 Citation (Scopus) -
Embedded multilevel monte carlo for uncertainty quantification in random domains
Badia, S., Hampton, J. & Principe, J., 2021, In: International Journal for Uncertainty Quantification. 11, 1, p. 119-142 24 p.Research output: Contribution to journal › Article › Research › peer-review
4 Citations (Scopus) -
Robust and scalable h-adaptive aggregated unfitted finite elements for interface elliptic problems
Neiva, E. & Badia, S., 1 Jul 2021, In: Computer Methods in Applied Mechanics and Engineering. 380, 26 p., 113769.Research output: Contribution to journal › Article › Research › peer-review
4 Citations (Scopus) -
The aggregated unfitted finite element method on parallel tree-based adaptive meshes
Badia, S., Martín, A. F., Neiva, E. & Verdugo, F., 8 Jun 2021, In: SIAM Journal on Scientific Computing. 43, 3, p. C203-C234 32 p.Research output: Contribution to journal › Article › Research › peer-review
5 Citations (Scopus) -
A generic finite element framework on parallel tree-based adaptive meshes
Badia, S., Martín, A. F., Neiva, E. & Verdugo, F., 18 Dec 2020, In: SIAM Journal on Scientific Computing. 42, 6, p. C436-C468 33 p.Research output: Contribution to journal › Article › Research › peer-review
4 Citations (Scopus)