• I am currently a Ph.D. student at the CRIStAL laboratory in the SigMA team in Lille, France, and the MAP5 laboratory in the probability team in Paris, France.
    I’m working on the subject: “stochastic methods for numerical integrations”, under the supervision of Rémi BARDENET and Raphael LACHIEZE-REY.
    I’m also winner of the challenge mathématiques et entreprise, organized by AMIES. We worked remotely with the company Foyer (Leudelange, Luxembourg), on assessing and improving data quality using machine learning methods (interview).
    I was a PGSM laureate in 2019/2020 for a master 2 grant at the University of Paris Cité, Paris, France.


  • Preprint, 2022

    On estimating the structure factor of a point process, with applications to hyperuniformity

  • Python Package, 2022

    structure_factor :

    CI-tests codecov docs-build docs-page PyPi version Python >=3.7.1,<3.10 Open In Colab

    An open-source Python package for studying the hyperuniformity of a spatial point process via the estimation of its structure factor.

    structure_factor contains:

    • Methods for sampling form a homogeneous Poisson point process, Thomas point process, Ginibre ensemble …
    • Methods for approximating the pair correlation function and the structure factor of a stationary point process
    • The first statistical test of hyperuniformity
    • The classical effective hyperuniformity test
    • Hyperuniformity class test

    The documentation of the package is published via the GitHub workflow file along with a tutorial Jupyter notebook. Any feedback is most welcome!