CV

Education

Ph.D in applied mathematics and scientific computing, Université de Bordeaux, 2020
M.S. in applied mathematics and scientific computing, Ensimag - Grenoble INP, 2017
B.S. in mathematics, Université de Bordeaux, 2015

Work experience

Postdoctoral researcher (Dec. 2023 - Today)
École Polytechnique Fédérale de Lausanne (Lausanne, Switzerland)
Suject: Dynamical low-rank approximations for data assimilation
Supervisor: Prof. Fabio Nobile
Postdoctoral researcher (Nov. 2021 - Nov. 2023)
Centre Inria de Paris (Paris, France)
Suject: Parameter estimation in blood flow model
Supervisors: Damiano Lombardi and Miguel A. Fernández
Postdoctoral researcher (Apr. 2021 - Oct. 2021)
Centre Inria de Bordeaux (Talence, France)
Suject: Extraction of the geometry associated with aortic aneurysms
Supervisor: Prof. Angelo Iollo
Scientific stay (Jan. 2020 - Apr. 2020)
Stanford University (Stanford, CA, USA)
Suject: Development of a space-local reduced-order model
Supervisors: Prof. Angelo Iollo and Prof. Charbel Farhat
Doctoral student (Oct. 2017 - Nov. 2020)
Université de Bordeaux (Talence, France)
Suject: Development of reduced-order models for fluid mechanics
Supervisor: Prof. Angelo Iollo

Skills

Programming languages: Maple, Matlab, Python, Julia, Fortran, C++.
Software and libraries: FreeFem++, OpenMP, MPI, ScaLAPACK, PETSc.

Publications

Robust high-order low-rank BUG integrators based on explicit Runge-Kutta methods

F. Nobile, S. Riffaud, "Robust high-order low-rank BUG integrators based on explicit Runge-Kutta methods", arXiv preprint arXiv:2502.07040 (2025).

Accurate and robust predictions for model order reduction via an adaptive, hybrid FOM/ROM approach

S. Riffaud, "Accurate and robust predictions for model order reduction via an adaptive, hybrid FOM/ROM approach", Journal of Computational Physics 523 (2025), p. 113677.

A low-rank solver for parameter estimation and uncertainty quantification in linear time dependent systems of Partial Differential Equations

S. Riffaud, M. A. Fernández, D. Lombardi, "A low-rank solver for parameter estimation and uncertainty quantification in time-dependent systems of Partial Differential Equations", Journal of Scientific Computing 99 (2024), no 2, p. 34.

Preconditioners for multilinear problems arising in parametric Partial Differential Equations

D. Lombardi, S. Riffaud, "Preconditioners for multilinear problems arising in parametric Partial Differential Equations", HAL preprint (2024).

Automatic branch detection of the arterial system from abdominal aortic segmentation

S. Riffaud, G. Ravon, T. Allard, F. Bernard, A. Iollo, C. Caradu, "Automatic branch detection of the arterial system from abdominal aortic segmentation", Medical & Biological Engineering & Computing 60 (2022), no 9, p. 2639–2654.

The DGDD method for reduced-order modeling of conservation laws

S. Riffaud, M. Bergmann, C. Farhat, S. Grimberg, A. Iollo, "The DGDD method for the reduced-order modeling of conservation laws", Journal of Computational Physics 437 (2021), p. 110336.

ROMs : convergence between HPC and data for fluid mechanics

S. Riffaud, "Reduced-order models: convergence between HPC and data for fluid mechanics", PhD thesis, Université de Bordeaux (2020).

Reduced-order model for the BGK equation based on POD and optimal transport

F. Bernard, A. Iollo, S. Riffaud, "Reduced-order model for the BGK equation based on POD and optimal transport", Journal of Computational Physics 373 (2018), p. 545-570.