About me

Research engineer, Uncertainty Quantification enjoyer, baking enthousiast.

You can download my CV by clicking on this sentence, or read a summary below.
Voici un lien pour mon CV (en français)

Research interests

Uncertainty quantification, Gaussian processes, kernel methods and reproducing kernel Hilbert spaces (RKHS), spatial statistics, inverse problems, active learning, sensitivity analysis, and optimization under uncertainty.

Professional experience

  • Research Engineer: Oct. 2024 – Present
    At ONERA – The French Aerospace Lab (Palaiseau, France). Research in uncertainty quantification and multidisciplinary optimization.
    • Surrogate modelling, active learning, and optimization under uncertainty for vehicle design.
    • Design of experiments and construction of simulation databases for surrogate modelling.
    • Sensitivity analysis and uncertainty quantification for computationally expensive numerical simulations.
    • Co-development and successful funding of an AID PhD project starting in 2027 on robust drone navigation using RKHS representations, with K. Dahia.
  • Adjunct Lecturer: Feb. 2025 – Present
    Master’s-level teaching, primarily in English.
    • At ENSAE Paris: tutorials for Theoretical Foundations of Machine Learning and Simulation and Monte Carlo Methods.
    • At ENSAI Rennes: supervision of a methodological project in statistics and artificial intelligence.

  • Postdoctoral Researcher: Sept. 2023 – June 2024
    At McGill University (Montréal, QC, Canada).
    Research in statistics and geostatistics: probabilistic modeling of mineral resources through itegration of expert knowledge and real drilling data.

  • Research and Teaching assistant: Nov. 2018 - June 2023
    At the institute of statistics and actuarial sciences, University of Bern (Bern, Switzerland).
    Until May 2020, the affiliation was shared with Idiap Research Institute (Martigny, Switzerland).
    • Research assistant with a strong focus on the Ph.D. topic. Active participation in scientific collaborations, proficiency in coding and creating reproducible examples using R language. Main research interests: Uncertainty Quantification, Gaussian Processes, Bayesian Optimization, Bayesian Statistics, Computer simulation models.

    • Senior consultant of the institute of statistics, University of Bern. Helping academics and companies planning and conducting statistical analysis (Jan. 2021 - Dec. 2023)

    • Teaching assistant for the institute of statistics at University of Bern:
      • R course (Fall term 2022).
      • Linear models I (Fall term 2022).
      • Spatial statistics (Spring term 2022).
      • Statistics for climate sciences I/II (Fall term 2019, Spring term 2020, Fall term 2020).
      • Optimization methods (Spring term 2019, Spring term 2023).
    • Co-supervisor (main supervisor: D. Ginsbourger) of the Master thesis: “Gaussian process regression on molecules: some performance assessments and comparisons”. (2021)
    • Teaching assistant in the continuing education program Master AI at Idiap Research Institute and Unidistance.
      • Foundations in statistics for AI (Spring term 2019 and 2020).
  • Research Intern: Mar. - Oct. 2018.
    At Idiap Research Institute (Martigny, Switzerland)
    Working on “Statistical and machine learning approaches to optimization problems under uncertainty arising in energy planning”, under the supervision of David Ginsbourger.

Education

  • Ph.D. in statistics, University of Bern (Bern, Switzerland), Nov. 2018 - June 2023
    Thesis: Modelling and Predicting Distribution-Valued Fields with Applications to Inversion under Uncertainty, supervised by Prof. David Ginsbourger.
    Awarded the highest possible grade and summa cum laude.

  • M.S. in Applied Mathematics, University Paris Dauphine (Paris, France), 2017 - 2018
    Specialization in statistical and financial engineering, statistics track.
    Graduated with highest honours and ranked first in the cohort.

  • M.Eng. in Data Sciences and Statistics, Ecole des Mines de Saint-Etienne, 2015 - 2018
    Ranked in the top 10% in the Statistics and Data Science specialization.
  • Preparatory classes, Lycée Henri IV (Paris, France), 2013 - 2015

Awards or distinctions

  • MASCOT-NUM 2022 annual meeting: Award for the best oral presentation.
  • University of Bern’s Fund for the Promotion of Young Researchers : Maximum grant award of CHF 5’000 to organize a workshop.
  • MASCOT-NUM 2021 annual meeting: Award for the best poster presentation.
  • SIAM (Society for Industrial and Applied Mathematics): Travel award for SIAM UQ 2022.

Academic service

  • Steering Committee member, RT-UQ, from Fall 2026.
  • In organizing committee : Lifting Inference with Kernel Embeddings 2023 June 26-30, 2023.
  • Main organizer of the workshop : Current frontiers in Gaussian Processes Aug. 24-26, 2022.
  • Lead organizerof the workshop : University of Bern–IMT Toulouse Workshop. May 3–4, 2022.
  • In organizing committee and webmaster : Lifting Inference with Kernel Embeddings 2022 Jan. 10-14, 2022.
  • Reviewer for AISTATS, NeurIPS, and SAMO.
  • Reviewer for Technometrics and the Journal of Multivariate Analysis.
  • Reviewer for the workshops Machine Learning and the Physical Sciences at NeurIPS and Synergy of Scientific and Machine Learning Modeling at ICML.