cat cv.md

Nathan Rousselot

PhD candidate (final year) · Arthemis team, LIRMM · Advanced Security Team, Thales (Thales Silicon Security, Meyreuil, France)

· scholar · linkedin · [cv.pdf: placeholder] · print this page for a pdf

status: open to ml-based security research / engineering roles from november 2027

Research

Publications

  • [2026] cascade

    Is it Really Broken? The Failure of DL-SCA Scoring Metrics under Non-Uniform Priors

    Nathan Rousselot, Karine Heydemann, Loïc Masure, Vincent Migairou, Rémi Strullu. CASCADE.

  • [2025] tches

    Scoop: An optimization algorithm for profiling attacks against higher-order masking

    Nathan Rousselot, Karine Heydemann, Loïc Masure, Vincent Migairou. IACR Transactions on Cryptographic Hardware and Embedded Systems.

  • [2024] ices jms

    Implementation of the split-beam function to Mills cross multibeam echo sounder for target strength measurements

    Guillaume Matte, Tehei Gauthier, Nathan Rousselot, Jean Guillard, Marie Lamouret, Olivier Lerda, Benoit Tallon, Phillipe Roux, Frederic Mosca. ICES Journal of Marine Science.

Posters & talks

  • [2026] poster

    Gradient-free Profiling for Deep Learning based Side-Channel Analysis against Masking: the Solution for the Plateau Effect?

    CHES 2026 · Antalya, Turkey

  • [2026] talk

    Solving Concealed ILWE by Graduated Non-Convexity: Recovering ML-DSA keys from side-channel leakage with fewer signatures

    JSCA 2026 · Montpellier, France

  • [2025] talk

    Reproducibility Challenges of Deep Learning-based Side-Channel Analysis

    OPTIMIST Workshop @ CHES 2025 · Kuala Lumpur, Malaysia

  • [2025] poster

    Scoop: An Optimization Algorithm for Profiling attacks against higher order masking

    PHISIC · Gardanne, France

  • [2025] talk

    SCOOP: une méthode d'optimisation de réseaux de neurones adaptée aux attaques par canaux auxiliaires

    GRETSI 2025

Teaching

  • fall 2026

    Foundations of Deep Learning

    Polytech Montpellier · M2 · course lead

  • spring 2027

    Random Signals

    Polytech Marseille · M1 · course lead

Experience

  • jun-dec 2021, jun-aug 2022

    Student researcher · IRIT

    Statistical processing of photoplethysmography signals (H. Goulart, M. Chabert); approximation of nonlinear physical models with Volterra-kernel methods (with W. Ghamour, sup. H. Goulart).

  • jun-sep 2023

    R&D intern · Exail, Sonar Division

    Large-scale statistical analysis of multibeam echo-sounder data (G. Matte, M. Lamouret).

Education

  • [dates: placeholder]

    MSc, Statistical Machine Learning for Information Processing

    ENSEEIHT (Toulouse INP)

  • [dates: placeholder]

    Exchange, Master of Mathematical Engineering

    KU Leuven

  • [dates: placeholder]

    Computer Engineering

    Efrei Paris