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 topic of interest include

From data and simulation to decision – Modelling creates uncertainty. This is a bad product: people mostly want to get rid of it. We help our partners to shift from the illusion of complete control to robust risk management and efficient decision processes.
Embracing complexity – Complexity also bears negative connotation. Yet, complex systems have emergent behaviours that go far beyond those of their parts: otherwise we would stick to hammer an nails kind of technologies (sometimes we should). We tackle this by dimension reduction, deep learning, and system scale (a.k.a. 0D/1D multi-physics) modelling.
From R&D to something else – Modelling is a tribal activity: a small group share tacit (=hard to transcribe) knowledge of great potential. Good ideas often lead to good R&D. Often, good R&D leads to… good ideas at best. We help partners to widen the innovation spiral and produce concrete outcomes.
AI, Animal Intelligence – Especially those of apes, and homo sapiens sapiens in particular (for lack of frequent contact with other species).

News¶

November 2024 – The 6th Researcher–Engineer Gathering, “Mathematical confluences, took place on 21st November 2022 at IHP. Presentations are available online at: https://seminaire.phimeca.com/. Thank you very much to all speakers and attendants.
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.

2024/10/14→17/ – λμ24 hosted by Institut de Maîtrise des Risques (IMdR). I presented the first results of the POLIVAL project: “’Uncertainty’: the elephant in the living rooom of soil pollution management?.” [🗎 get slides]
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”.