CV

Education

• PhD in Applied Mathematics / Scientific Machine Learning, CNAM (Conservatoire National des Arts et Métiers), Paris, 2021–2024
  • Machine learning strategies for accelerating numerical simulations of fluid-structure interaction
  • Supervised by Pr. I. Mortazavi, Pr. F. De Vuyst, T. Dairay, J-P. Berro Ramirez
  • HAL Id: tel-05269807
• Summer School – Scientific Machine Learning, CEMRACS 2023, CIRM, Marseille, July 2023
• Mechanical Engineering Degree, ENSAM (École Nationale Supérieure d’Arts et Métiers), Paris, 2017–2021
  • Silver Medal – Rank: 83/1180

Work Experience

• Computational R&D Engineer — Michelin, Clermont-Ferrand (Dec 2024 – Present)
  • Part of a team developing and modernizing a large-scale industrial finite element framework. <!– designed for massively parallel HPC environments
  • Led the development of a coupling interface between the parallel solver and ML-based external packages, ensuring MPI scalability across the integration layer (mpi4py)
  • Developed advanced tyre simulation features with complex boundary conditions handling
  • Supervised an internship on fluid-structure interaction simulations –>
• PhD Student — Research Engineer — M2N, CNAM / Michelin / Altair, Paris (Nov 2021 – Oct 2024)
  • Machine Learning-based Reduced Order Models (ROMs) for fluid-structure interaction (FSI)
  • Studied and extended data-driven system identification methods
  • Developed new techniques to couple ROMs and classical methods for FSI simulations
  • Developed ML-based methods to accelerate convergence of FSI coupling algorithms
  • Contributed to open-source scientific software and maintained in-house ROM packages
  • Published 2 journal articles and multiple international conference communications
• Visiting PhD Student — Esteco (previously Optimad), Turin (Feb 2024 – Mar 2024)
  • Explored stability properties of data-driven reduced order models
• Substitute Teacher — CNAM, Paris (Sep 2022 – Jan 2024)
  • Taught practical work on Numerical Methods, Fluid Mechanics and Functional Analysis
• Simulation Research Engineer (Master’s Thesis) — Dassault Systèmes, Vélizy-Villacoublay (Mar 2021 – Aug 2021)
  • Data-Driven Computational Mechanics (DDCM)
  • Studied numerical convergence and extension to non-elastic and multiscale problems
  • Extended the approach using manifold learning and noisy optimization techniques
  • Developed in-house code and its coupling with a finite element solver
• Simulation Software QA Intern — Coventor Inc. (Lam Research), Villebon-sur-Yvette (Jun 2020 – Aug 2020)
  • Wrote tests for meshing features of MEMS+, involving numerical analysis and electromechanical modeling

Technical Skills

• Programming: Python, C++, C, Matlab
• Scientific Computing: PETSc, KratosMultiphysics, FEniCS, scikit-fem, NumPy, PyTorch, scikit-learn, PyVista, Paraview
• Tools: Git, Linux, LaTeX
• Scientific Expertise: Linear Algebra, Dynamical Systems, Nonlinear Solvers, Computational Mechanics, Finite Element Method, Multiphysics Coupling, Reduced-Order Modeling, Manifold Learning

Languages

• English (TOEIC: 985/990)
• French
• Arabic

Publications

Machine Learning to Accelerate Fluid-Structure Interaction Simulations

Azzeddine Tiba, Thibault Dairay, Florian De Vuyst, Iraj Mortazavi, Juan Pedro Berro Ramirez. (2025). "Machine Learning to Accelerate Fluid-Structure Interaction Simulations." FSSIC 2025 Symposium Proceedings.

Machine-learning enhanced predictors for accelerated convergence of partitioned fluid-structure interaction simulations

Azzeddine Tiba, Thibault Dairay, Florian De Vuyst, Iraj Mortazavi, Juan Pedro Berro Ramirez. (2025). "Machine-learning enhanced predictors for accelerated convergence of partitioned fluid-structure interaction simulations." Computer Physics Communications. 310, 109522.

Non-intrusive reduced order models for partitioned fluid-structure interactions

Azzeddine Tiba, Thibault Dairay, Florian De Vuyst, Iraj Mortazavi, Juan-Pedro Berro Ramirez. (2024). "Non-intrusive reduced order models for partitioned fluid–structure interactions." Journal of Fluids and Structures. 128, 104156.

Dynamical Data-Driven Model Order Reduction for nonlinear Fluid-Structure Interaction problems

Azzeddine Tiba, Thibault Dairay, Florian De Vuyst, Iraj Mortazavi, Juan Pedro Berro Ramirez. (2022). "Dynamical Data-Driven Model Order Reduction for nonlinear Fluid-Structure Interaction problems." 25è Congrès Français de Mécanique. pp. 151-158.

Talks

SPARCL Workshop

April 08, 2026

Talk at SPARCL Workshop, Paris, France

37ème Séminaire de mécanique des fluides numérique

January 01, 2025

Talk at SMAI-GAMNI, IHP, Paris, France

ICCE Conference

October 01, 2024

Invited Talk at ICCE Conference, Darmstadt, Germany

ECCOMAS

June 15, 2024

Invited Talk at ECCOMAS, Lisbon, Portugal

CEACM S4ML Conference

June 01, 2024

Invited Talk at CEACM S4ML Conference, Prague, Czech Republic

ERCOFTAC

June 07, 2023

Invited Talk at ERCOFTAC, Toulouse, France

SIA Simulation Numérique

April 01, 2023

Talk at SIA Simulation Numérique, Champs-sur-Marne, France

1st Aria Workshop

March 01, 2023

Invited Talk at 1st Aria Workshop, Bordeaux, France

CANUM

June 13, 2022

Invited Talk at CANUM, Evian-les-Bains, France

Teaching

Numerical Methods, Fluid Mechanics and Functional Analysis

Gallery

• PhD Thesis — Video Abstract: An illustrative summary of the main contributions of my PhD thesis on ML-accelerated fluid-structure interaction simulations. Watch the video