Solange Pruilh

Ph.D in Statistics and Machine Learning

I am a postdoc in Jordi Merino's group at CBMR, University of Copenhagen. I develop deep learning models for multimodal data, including continuous glucose monitoring signals, to uncover new phenotypes and behaviours in healthy populations. I am particularly interested in real-world applications of machine learning in clinical settings.
I have a Ph.D. in applied mathematics, specifically in statistics and machine learning. I completed it at CMAP (Ecole Polytechnique) and HeKA (PariSanteCampus), under the supervision of Stéphanie Allassonnière and Anne-Sophie Jannot. My research focused on statistical learning algorithms, mixture models, and applications to public health data.

News

Apr 27, 2026	I co-organized the SMARTbiomed Symposium on Machine Learning for Longitudinal and Multi-omics Data, held on April 27–28 at the University of Copenhagen! 🎉 A great two days of talks and discussions bringing together researchers working at the intersection of machine learning and biomedical data.
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
Sep 28, 2023	I defended my Ph.D thesis! 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
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	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, K.A. 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, K.A. 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

2025–ongoing: SMARTbiomed fellow and postdoc at CBMR, University of Copenhagen, Denmark
2019–2023: Ph.D. student at CMAP, Ecole Polytechnique and HeKA team, INRIA/INSERM, France
April–August 2019: Statistics research intern at CMAP and HeKA team, France
February–July 2018: Data science intern at Wavestone, in the Machine Learning & Data Lab, Paris, France
July–September 2017: Statistics research intern with Kim-Anh Lê Cao at Melbourne Integrative Genomics, University of Melbourne, Australia

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

Service & Leadership

Co-organized the SMARTbiomed Symposium on Machine Learning for Longitudinal and Multi-omics Data, hosted at KU, Copenhagen
Co-organized the 1st edition of National Seminar for Young French Applied Mathematicians (CJC-MA) in October 2021
Former member of Commission Développement Durable at CMAP
Former member of Commission Vie de Laboratoire at CMAP
Vice President of INSA Toulouse’s junior company during my engineering studies

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