Curriculum Vitæ

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Education & professional experience

  1. 2022 – 2026

    PhD in Mathematics

    Inria (Team McTAO) — Université Côte d'Azur, Laboratoire J.A. Dieudonné (LJAD)

    Thesis (defended 2 July 2026): State and parameter estimation of neural mass and mean-field models: a control-theoretic approach. Supervisors: Jean-Baptiste Pomet, Dario Prandi, Ludovic Sacchelli.

  2. 2019 – 2022

    Master of Mathematics & Applications — Mathematics of Modeling

    Sorbonne University, with École Polytechnique and École Nationale des Ponts et Chaussées

    Research internship at L2S — CentraleSupélec, Paris-Saclay University: Identification of illusory state in the visual cortex. Supervisors: Dario Prandi, Jean-Baptiste Pomet, Ludovic Sacchelli.

  3. 2017 – 2019

    Bachelor's Degree in Mathematics — Intensive Track

    Sorbonne University

  4. 2015 – 2017

    Preparatory Classes for the “Grandes Écoles” (CPGE)

    Algiers, Algeria

Conferences & talks

  • IEEE Conference on Decision and Control (CDC)

    Rio de Janeiro, Brazil · Dec 2025

    Talk — “Identification of saturated networked systems.”

  • IEEE Conference on Decision and Control (CDC)

    Milan, Italy · Dec 2024

    Talk — “Homogeneous observer for a low-dimensional neural fields model of cortical activity.”

  • NeuroPSI–Chen Institute Conference

    Saclay, France · May 2024

    Poster — “Neuroengineering for Exploring and Repairing the Brain.”

  • Complex Days — Complex Systems Academy, Université Côte d'Azur

    Nice, France · Feb 2024

    Poster presentation.

  • NOCCA — Nonlinear and Optimal Control on the Côte d'Azur

    Sophia Antipolis, France · Sep 2026

    Participation.

Summer & autumn schools

  • EECI International Graduate School on Control (IGSC)

    Cagliari, Italy · Jun 2023

    An overview on observer design methods for nonlinear systems — P. Bernard, V. Andrieu, D. Astolfi.

  • EITN–EBRAINS Fall School in Computational Neuroscience

    Marseille, France · Oct 2024

    10-day course — from cellular models to whole-brain dynamics.

Teaching

Teaching Assistant — Mathematics (96 h), Laboratoire J.A. Dieudonné, Université Côte d'Azur.

Technical skills

Programming
Python · Julia · LaTeX · Git
Machine learning & deep learning
NumPy · SciPy · scikit-learn · PyTorch · TensorFlow / Keras

References