Sylvain Girard’s scientific page¶

I lead the “Reliability & Robustness” team at Phimeca Engineering Paris.

We use data science and numerical simulation to help designing, operating and maintaining industrial system safely and efficiently.

My main research interest are

Uncertainty modelling, in particular of spatio-temporal phenomena. Applications include pollution diagnosis and forecast, and health monitoring of industrial systems.
Dimension reduction and function approximations.
System scale modelling (also known as 0D/1D in some engineering comunities).

I’m hiring! See the job offer (in french) here: [🗎 download pdf] system modelling

News¶

November 2024 – The 6th Researcher–Engineer Gathering, “Mathematical confluences, will be held 21st November 2022 at IHP. The program is being updated gradually: https://seminaire.phimeca.com/. Please write me an email (←) if you would like to give a talk.
December 2023 – Actor Network Theory meets Geostatistics?! ADEME funds the POLIVAL project, starting in January 2024. Objective: Optimize decisions for recovering polluted sites and industrial wastelands.
December 2023 – There is a new item to Phimeca’s “showroom”. Have a look at our interactive demo of dimension reduction method “From Principal Component Analysis (PCA) to Auto-Associative model (AAM)”. Programmed by Valentin Pibernus.

2024/10/14→17/ – λμ24 hosted by Institut de Maîtrise des Risques (IMdR). I’ll present the first results of the POLIVAL project: ““Uncertainty”: the elephant in the living rooom of soil pollution management?. ”
2024/6/14 – 17th OpenTURNS’ Users Day. OpenTURNS is an open source python module for statistics and machine learning. I talked about the OtFMI module, a two-way interface to the FMI model exchange standard [🗎 get slides].
2024/3/20 – Round table at the Nuclear Science and Technic Days (JSTN, Journées des sciences et techniques nucléaires) organized by EAMEA: “AI & nuclear safety: for a better risk perception”.
2023/10/26 – PHM 2023 Francesco Cancelliere gave this talk:“A Grey Box approach for the Prognostic and Health Management of Lithium-Ion Batteries” [🗎 get paper].