Welcome to my personal page
I am currently working at Zelros AI as a machine learning researcher. Prior to that I was a PhD student at LPSM under the supervision of Olivier Lopez (LPSM).
My fields of research used to be survival analysis, machine learning for censored data and applications to insurance. I am currently working on monitoring and ethical aspects of machine learning, with a special focus on data drift.
Publications
Journal
- G. Gerbert, Y. Le Faou, O. Lopez, M. Trupin (2020). The impact of churn on client value in health insurance, evaluation using a random forest under random censoring. Journal of the American Statistical Association.
[code] • [talk - IME 2017] • [poster - Mascot Num 2017]
Preprint
- Y. Le Faou, O. Lopez (2018). A nonparametric conditional copula model for successive duration times, with application to insurance subscription. Preprint.
[code] • [poster - DS3 2018]
PhD thesis
- Y. Le Faou (2019). Contributions à la modélisation des données de durée en présence de censure : application à l'étude des résiliations de contrats d'assurance santé.
Softwares
- CinnaMon (2021), a Python library for the monitoring of machine learning systems that focus on data drift. See the github and the video presentation in french (slides here).
- sword (2018), a R package to fit regression models to right censored data. See the github and the package vignette.
email : lefaou [dot] yohann [at] gmail [dot] com