Researcher at Criteo AI Lab. Deep Learning, generative models, dynamical systems.
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Assessing your cultural and operational fit
Criteo
Data Scientist
June 26, 2026 – Present
fairness-cards
May 28, 2026 – Present
Reproducibility artifact for the ICML 2026 position paper 'Fairness Failure in Generative Models is an Evaluation Problem' (Vladimirova, Franceschi, Issenhuth).
View Projectgpm
May 25, 2023 – January 5, 2025
Official implementation of the paper "Unifying GANs and Score-Based Diffusion as Generative Particle Models", NeurIPS 2023
View ProjectDINo
October 5, 2022 – January 13, 2024
Time- and space-continuous neural PDE forecaster based on INRs and ODEs - ICLR 2023
View Projectspatiotemporal_variable_separation
August 3, 2020 – March 15, 2021
Official implementation of the paper *PDE-Driven Spatiotemporal Disentanglement*
View Projectsrvp
February 14, 2020 – March 29, 2022
Official implementation of the paper Stochastic Latent Residual Video Prediction
View ProjectUnsupervisedScalableRepresentationLearningTimeSeries
January 28, 2019 – July 31, 2024
Unsupervised Scalable Representation Learning for Multivariate Time Series: Experiments
View ProjectSMABP
October 29, 2017 – November 15, 2017
Small implementation of strategies in the Stochastic Multi-arm Bandit Problem
View ProjectPointSetAnalyser
July 22, 2016 – July 22, 2016
An analyser of 2D sampling patterns for computer graphics.
View ProjectCultural Fit Analysis
The candidate's project portfolio is heavily skewed towards academic research and personal projects, primarily in advanced machine learning and computer graphics. While demonstrating strong technical depth, the lack of diverse project types (e.g., team-based, production-oriented, business-focused) makes it difficult to fully assess cultural fit for a typical industry Data Scientist role. The current role at Criteo as a Data Scientist aligns with the target role, but no details are provided regarding responsibilities or team collaboration.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate a strong focus on research and technical implementation.