Nathan Noiry is a postdoctoral researcher in the LTCI S2A Research Team (Signal, Statistics and Learning).
He is working on survey sampling, transfer learning and broadly speaking on machine learning problematics.
After studying at Ecole Normale Supérieure de Lyon, he completed a PhD in probability theory,
during which he worked on random matrices and random graphs.
Key words: machine learning, survey sampling, transfer learning, random matrices, random graphs