Clara Carlier, PhD

Clara Carlier, PhD

Research engineer in Applied Mathematics - specialized in Statistics, Machine Learning and Deep Learning

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About me

I’m currently working as a research engineer in statistics and data science at the Laboratoire national de métrologie et d’essais (LNE) in Trappes (78). I am part of the Data Science and Uncertainty team.

Previously, I’ve finished my industrial PhD. It was a collaboration between the CREST-ENSAE laboratory at the Institut Polytechnique de Paris and the Renault group. I was supervised by Matthieu Lerasle and Arnaud Franju.
The PhD was about Calibration of models to build the digital twin of the autonomous vehicle. It involved various methods such as supervised learning and classification, as well as Bayesian inference using Approximate Bayesian Computation methods.

Before my PhD, I graduated from the Master 2 in Mathematics of Randomness, specializing in Statistics and Machine Learning, at the Université Paris-Saclay in Orsay, France.

For more details, see CV (FR).

Student supervision

  • (2023, end-of-study project) Rayan Maaloul, Construction of a generative time series model using Deep Learning methods (Renault group, co-supervised with Arnaud Franju)

Award

Volunteering

  • (2021-2023) Doctoral student representative on the Hadamard mathematics graduate school (EDMH) board, Orsay, France
  • (2015-2018) Student representative on the Paris-Sud University bachelor’s degree development committee, Orsay, France
  • (2018) In charge of applications for the Data’Bang edition of TEDx Saclay, Orsay, France

Reviewing service

  • (2023) International Conference on Machine Learning (ICML)
  • (2023) Neural Information Processing Systems (NeurIPS)

Conferences