CV

Contact: sylvain.combettes [a t] ens-paris-saclay.fr

You can also look into my publications, my talks, and my teaching experience in their according tabs.

Professional experience

Feb. 2024 – present	École Normale Supérieure Paris-Saclay	Postdoctoral researcher	Paris area, France
	I am a postdoctoral researcher at the Centre Borelli research lab under the supervision of Laurent Oudre. Pedagogical engineer and product manager for the BrevetAI of SaclAI-School (DATAIA Institute), an educational platform for AI acculturation through a learning-by-doing approach, aimed at students of the University of Paris-Saclay. The team consists of 10 members, including pedagogical engineers, developers, UX/UI designers, etc.
Mar. – Aug. 2020 (6 months)	Artefact	Data Scientist intern	Paris, France
	Consulting for a major player in the food industry: demand sensing for new products with very few historical sales data ("cold start"). Involved throughout the whole pipeline in agile development: exploratory data analysis, model iteration, production, industrialisation, and delivery. Technologies: AWS, Dask, Docker, Git, Pandas, Prophet, Unix, scikit-learn, statsmodels, tslearn. Result: The method developed for a specific country, in pairs with a Senior Data Scientist, was a success and was being deployed in other countries at the end of my internship. Links: Medium blog.
June – Sep. 2019 (3 months)	Servier	Data Scientist intern	Paris area, France
	Topic: Generating fictitious realistic patient data with generative adversarial networks (GANs). Result: I show that a new simulation method for the Choquet integral is "correct". Links: report, slides, GitHub, Medium blog.

Education

Oct. 2020 – Jan. 2024	École Normale Supérieure Paris-Saclay	Doctor of Philosophy (PhD)	Paris area, France
	Mathematics / Data Science applied to time series. Thesis title: Symbolic representations of time series. Advisors: Laurent Oudre and Charles Truong, Centre Borelli (Université Paris-Saclay, CNRS, ENS Paris-Saclay). PhD successfully defended on January 8th, 2024. Committee: Mathilde Mougeot (Présidente), Germain Forestier (Rapporteur & Examinateur), Romain Tavenard (Rapporteur & Examinateur), Themis Palpanas (Examinateur), and Patrick Schäfer (Examinateur). Extra activities: Co-organizer of the Machine Learning and Massive Data Analysis (MLMDA) weekly seminars with external or internal speakers in 2022/2023. Supervision of a research internship for a normalien student from the Mathematics Department (Mar. - June 2022).
2017 – 2020	École des Mines de Nancy	Master of Science	Nancy, France
	Big Data & Data Science track within the Department of Mathematical Engineering. Awarded the Saint-Gobain Research Excellence Scholarship 2020 for academic achievements.
2014 – 2017	Lycée Louis-le-Grand	Classe Préparatoire aux Grandes Écoles	Paris, France
	Intensive preparation for the highly selective entrance examination to the Grandes Écoles (leading national French schools of Engineering). Filière PCSI/PC*: Advanced Mathematics, Physics, Chemistry, Philosophy and English.
2011 – 2014	Lycée Louis-le-Grand	Baccalauréat général avec la mention très bien	Paris, France
	At the end of high school, I received the Baccalauréat (main French diploma required to pursue university studies) in Science with Highest Honors.

Past projects

Oct. 2019 – Feb. 2020 (5 months)	École des Mines de Nancy	Research project in Data Science	Nancy, France
	Topic: Comparison of empirical probability distributions using integral probability metrics and $f$-divergences. Result: I show that a new simulation method for the Choquet integral is "correct". Links: report, slides, GitHub.
Oct. 2018 – June 2019 (9 months)	Saint-Gobain	Research project in Data Science	Paris area, France
	Topic: Anomaly detection using principal component analysis (PCA) and Gaussian kernel PCA. Result: the algorithm can detect 100% of the failure days observed by operators from Saint-Gobain. Links: GitHub.