Ali ABBOUD

Research and Development Engineer

PhD in Applied Mathematics from École Polytechnique and the Atomic Energy Commission, dedicated to applying statistics, numerical analysis, and computational modeling to solve complex engineering challenges with innovative, data-driven solutions.

About Me

I hold a PhD in Applied Mathematics from École Polytechnique (Centre of Applied Mathematics) and the French Atomic Energy Commission (CEA).

My research focused on developing a methodology for uncertainty quantification, with the goal of improving the accuracy and predictivity of fluid-structure interaction simulations in nuclear reactors.

Along the way, I've built an experience in: Statistics, Probability, Mechanics, Thermal-hydraulics, Neutronics, Numerical methods

Beyond my core research, I'm also very interested in quantitative finance, especially in roles that involve quantitative research and data-driven decision-making.

My PhD was directed by Professor Josselin Garnier and supervised by Bertrand Leturcq and Stanislas de Lambert, researchers at the CEA.

6+ Publications

Published in top-tier journals and conferences

3+ Years

Experience in research and teaching

Best Paper Award

Best Estimate Plus Uncertainty International Conference

Experience

My professional journey spans research, teaching, and engineering.

PostDoctoral Researcher

CMAP, École Polytechnique

Oct 2025 - Apr 2026

Centre of Applied Mathematics (CMAP), École Polytechnique, under the supervision of Professor Josselin Garnier.

Proposed and validated an uncertainty-quantification framework for nonlinear coupled systems where each solver is modeled via Gaussian Process (GP) regression and the global interaction is solved through a fixed-point iterative algorithm

Developed a Monte Carlo estimator for coupled fixed-point systems, based on deterministic mean-path evaluation and constant-offset perturbations of GP posterior means, avoiding full functional sampling over continuous input spaces.

Established finite-sample probabilistic guarantees by linking GP posterior covariance structure to design fill distance, extending to multi-output models via a Linear Model of Coregionalization (LMC) kernel, and combining this with Lipschitz stability analysis of the coupled solution operator.

Benchmarked the estimator against a trajectory-conditioned sampling procedure, assessing distributional fidelity, bias–variance characteristics, and computational scalability.

Applied the methodology to a coupled fluid–structure interaction system for structured uncertainty propagation and global sensitivity analysis.

PhD Researcher

CEA and École Polytechnique

Oct 2022 - Sep 2025

French Atomic Energy and Alternative Energies Commission (CEA), Mechanical and Thermal Studies Department.

Developed an uncertainty-quantification framework for multi-physics fuel-assembly bow simulation in pressurised water reactors, combining hydraulic and thermomechanical models.

Step 1 – Hydraulic modeling: Conducted variance-based global sensitivity analysis (Sobol decomposition) to quantify variance contributions and identify the dominant input parameters. Built a high-dimensional Gaussian Process (GP) surrogate for the nonlinear hydraulic solver, achieving Q² ≈ 0.94.

Step 2 – Mechanical modeling: Applied the same Sobol-based sensitivity analysis and GP regression framework to the thermomechanical solver. Developed a stochastic surrogate with Q² ≈ 0.98 and < 2% validation error across stress-test configurations.

Main contribution – Coupled stochastic surrogate models: Designed a fixed-point coupling algorithm integrating hydraulic and mechanical GP surrogates, with stability supported by operator-level analysis and contraction-type arguments.

Reduced full-cycle simulation time from 4 hours to 2 minutes (~100× acceleration) while preserving distributional accuracy.

Quantified coupling-induced modeling error through residual and distributional comparisons, showing negligible deviation relative to the physical deformation scale (0.24 mm numerical deviation vs 12 mm system deformation).

Final stage – Full-system uncertainty analysis: Performed large-scale Monte Carlo uncertainty propagation on the coupled nonlinear system, combined with global sensitivity analysis, to characterize output distributions and identify the main drivers of variability.

Algorithm Developer

Komission.fr

Sep 2024 - Present

Komission is the first fully digital broker specializing in payment services and solutions, both online and in-store. Founded with the goal of supporting merchants with diverse needs, Komission aims to simplify and accelerate the process of selecting the best payment service provider.

Development of a payment method comparison algorithm for Komission.fr

Algorithm design and optimization for payment service provider matching

Data analysis and comparison metrics implementation

Python programming and financial technology solutions

Teaching Assistant

HEC Paris

2023 - Present

Teaching Assistant

École Polytechnique

2024 - 2025

Engineering Intern

French Atomic Energy and Alternative Energies Commission (CEA)

Mar 2022 - Sep 2022

Reactor Studies and Applied Mathematics Department – SERMA

Development and Comparison of Finite Element Bases for a Neutron Transport Equation on a Hexagonal Mesh.

Finite Element Method, Discontinuous Galerkin Method, Neutronics.

Python · Object-Oriented Programming.

Publications

Selected publications from my research career.

Uncertainty Quantification in Coupled Multiphysics Systems via Gaussian Process Surrogates: Application to Fuel Assembly Bow

2026

Ali Abboud, Stanislas de Lambert, Josselin Garnier, Bertrand Leturcq

International Journal for Uncertainty Quantification

Uncertainty quantification

Gaussian Process Regression

Fuel Assembly bow

Fluid-Structure interaction

Uncertainty quantification applied to fuel assembly bowin a pressurized water reactor

2025

Ali Abboud

École Polytechnique

Uncertainty quantification

Metamodeling

Thermomechanics

Thermohydraulics

Fuel assembly bow

Multifidelity

Towards Uncertainty Quantification: Efficient Surrogate Models In Coupled Fluid-Structure Interaction For Fuel Assembly Bow

2025

Ali Abboud, Josselin Garnier, Bertrand Leturcq, Nicolas Lamorte, Stanislas de Lambert

International Conference on Probabilistic Safety Assessment and Analysis (PSA 2025). Chicago, IL, USA. June 15–18, 2025

Uncertainty Quantification

Surrogate Models

Fluid-Structure Interaction

Uncertainty Quantification Of Fuel Assembly Bow In Pressurized Water Reactor Through a Thermomechanical Simulation

2025

Ali Abboud, Josselin Garnier, Bertrand Leturcq, Julien Pacull, Olivier Fandeur, Stanislas de Lambert

M&C 2025 - The International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering. Denver, Colorado, USA. April 27–30, 2025

Uncertainty Quantification

Thermomechanical Simulation

Nuclear Engineering

Sensitivity Analysis of a Flow Redistribution Model for a Multidimensional and Multifidelity Simulation of Fuel Assembly Bow in a Pressurized Water Reactor

2024

Ali Abboud, Stanislas de Lambert, Josselin Garnier, Bertrand Leturcq

Best Estimate Plus Uncertainty International Conference (BEPU 2024). Real Collegio, Lucca, Tuscany, Italy. May 19–24, 2024

Sensitivity Analysis

Flow Redistribution

Best Paper Award

Teaching

My teaching experience and courses taught.

Teaching Assistant

École Polytechnique, Palaiseau, Île-de-France, France

Sep 2024 – Present

Applied Mathematics: Series Theory, Differential Equations, Probability
Variational Analysis of Partial Differential Equations (Finite Element Method)

Teaching Assistant

HEC Paris, Jouy-en-Josas

Aug 2023 – Present

Data Analysis for Master's Student

Education

My academic background and qualifications.

PhD in Applied Mathematics

École Polytechnique, Palaiseau, France

2022 - 2025

Focusing on uncertainty quantification and computational modeling for nuclear engineering applications

Master's Degree in Mathematics and Applications

University of Reims Champagne Ardenne, Reims, France

2020 - 2022

Scientific Computing Track

Master's Degree in Fundamental Mathematics

Lebanese University, Beirut, Lebanon

2019 - 2020

Bachelor's Degree in Fundamental Mathematics

Lebanese University, Beirut, Lebanon

2015 - 2019

Skills

Technical expertise and competencies.

Mathematics

Statistics & Probability

Machine Learning

Numerical Analysis of PDEs

Finite Element Method

Mathematical Modeling

Optimization

Computer Skills

C/C++

Fortran

Python

R Language

FreeFem++

Languages

Arabic (Native)

English (Fluent)

French (Fluent)

Contact Me

Get in touch for collaborations, research opportunities, or questions about my work.

Email

ali.abboud@polytechnique.edu

ali.ib.abboud95@gmail.com

Phone

+33 782506850

Address

Paris, France