Fellow | Mathieu Carrière

Mathieu Carrière is a permanent research scientist (CRCN) in the DataShape team at Centre Inria d'Université Côte d'Azur. Prior to this, he did his PhD at Inria Saclay in the DataShape team, under the supervision of Steve Oudot, and a postdoc of two years in the Rabadán Lab, at the Department of Systems Biology of Columbia University, under the supervision of Raúl Rabadán. His research focuses on topological data analysis and statistical machine learning, with an application to bioinformatics and genomics. He is also part of the editorial board of the Gudhi library, which is the reference library for topological data analysis.

The central tenet of the TopMoDaL project is that multiparameter topological data analysis (mTDA) has the potential to become an important asset for most standard machine learning (ML) models and pipelines. The aim of the project is to drastically improve the predictive and/or generative powers of ML models by providing both new descriptors and new regularization and monitoring tools from mTDA, that can be applied on many types of complex data.