Since October 2021, I am a Postdoctoral researcher of the 3iA Côte d’Azur at Centre Inria d’Université Côte d’Azur in the Maasai team. I am now working on semi-supervised learning, with Charles Bouveyron and Pierre-Alexandre Mattei.
The goal of this PhD thesis was to propose new statistical methods to handle missing values in several supervised and unsupervised machine learning scenarios, particularly when the data can be Missing Not At Random (MNAR), i.e. when the unavailability of values depends on the missing values themselves and values of other variables. We have considered low-rank models (fixed and PPCA), online linear regression using SGD and model-based clustering.
Here you can find my detailed resume.
I am very happy to present my work to the 3iA Seminar soon (April 1. 2022, it is not a joke) !
Resource website on missing values: I am still maintaining our platform on missing values R-miss-tastic, do not hesitate to contact me if you have questions or if you want to contribute ! It is an on-going and collaborative project !
Workshop Missing Data and Survival Analysis: in June, I will give a talk in Angers (France) about Missing Not At Random values in the semi-supervised learning context.
I will present a poster in Statlearn about Missing Not At Random values in the semi-supervised learning context.