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Novo Nordisk Foundation Center for Basic Metabolic Research

Blegdamsvej 3B, Mærsk Tårnet

Copenhagen N.

Solange Pruilh

Ph.D in Statistics and Machine Learning

I am a postdoc in Jordi Merino's group at CBMR, University of Copenhagen. I am working on using continuous glucose monitoring data to explore heterogeneity and patterns in healthy individuals, with the aim of early detection of profiles leading to type 2 diabetes.
I have a Ph.D. in applied mathematics, and especially statistics and machine learning. I did it at CMAP (Ecole Polytechnique) and HeKA (PariSanteCampus), under the supervision of Stéphanie Allassonnière and Anne-Sophie Jannot. My research project was mainly about statistical learning algorithms, mixture models, and applications to public health data.


News

Feb 1, 2025 I start working as a postdoc with Jordi Merino at Novo Nordisk Foundation Center for Basic Metabolic Research, within the Health and Medicine faculty of the University of Copenhagen :denmark:
Sep 28, 2023 I defended my Ph.D thesis! :sparkles: Thanks to the members of the jury and to my Ph.D supervisors. You can find my manuscript here
Jul 3, 2023 I attended the Journées de Statistique de la SFdS 2023 conference, in Bruxelles in July 2023 :fries:
Jun 14, 2022 I attended the Journées de Statistique de la SFdS 2022 conference, in Lyon, and presented my work on spatio-temporal mixture processes
Apr 3, 2022 I attended the Rencontres des Jeunes Statisticien.ne.s 2022 conference, in Porquerolles, and presented my work on spatio-temporal mixture processes
Feb 16, 2022 :page_with_curl: Our paper Spatio-temporal mixture process estimation to detect dynamical changes in population was accepted in Artificial Intelligence in Medicine




Publications

  • Pruilh, S, & Allassonnière, S. (2024). Dynamic Expectation-Maximization algorithms for Mixed-type Data.[Preprint]

  • Pruilh, S (2023). Dynamic mixture models and longitudinal monitoring for mixed-type and spatio-temporal data inference : application in Public Health. [Manuscript]

  • Pruilh, S., Jannot, A. S., & Allassonnière, S. (2022). Spatio-temporal mixture process estimation to detect dynamical changes in population. Artificial Intelligence in Medicine, 126, 102258.[Paper]

  • Dashper, S.G., Mitchell, H.L., Lê Cao, KA. et al. (2019). Temporal development of the oral microbiome and prediction of early childhood caries. Sci Rep 9, 19732. [Paper]

  • Matsuyama, M., Morrison, M.,Lê Cao, KA. et al. (2019). Dietary intake influences gut microbiota development of healthy Australian children from the age of one to two years. Sci Rep 9, 12476. [Paper]

Work Experience

  • 2019-2023: Ph.D. student at CMAP, Ecole polytechnique and HeKA team, INRIA/INSERM
  • April-August 2019: Statistics research intern at CMAP and HeKA team
  • February-July 2018: Data scientist intern at Wavestone company, in Machine Learning & Data lab
  • July-September 2017: Statistics research intern with Kim-Anh Lê Cao at Melbourne Integrative Genomics, University of Melbourne.

Education

  • 2019-2023: Ph.D. at CMAP, Ecole polytechnique and HeKA team, INRIA/INSERM
  • 2018-2019: MSc. at ENS Paris-Saclay, M2 MVA
  • 2013-2018: Engineering degree in applied mathematics at INSA Toulouse - Major in statistics and data science

Teaching

2021-2022
  • Registration and Segmentation (MAA308 and MAA309, École polytechnique, 3rd year Bachelor)
  • Supervised a Bachelor thesis on Variational Auto-Encoders
2020-2021
  • Registration and Segmentation (MAA308 and MAA309, École polytechnique, 3rd year Bachelor)
  • Regression (MAP535, Ecole polytechnique, Data Science Master with HEC)
2019-2020
  • Registration and Segmentation (MAA308 and MAA309, École polytechnique, 3rd year Bachelor)
  • Assistant to evaluate PSC projects

Miscellaneous