Name:Nicolas Keriven

Bio:

Nicolas Keriven is a CNRS researcher in signal processing and machine learning with the COMPACT team at IRISA (Rennes, France). His research interests include machine learning and signal processing on graphs, graph neural networks (GNNs), random graphs, dimensionality reduction, and sparsity.

He graduated from École polytechnique (Palaiseau, France) and obtained the Mathématiques, Vision, Apprentissage (MVA) Master’s degree from École Normale Supérieure de Cachan in 2014. He completed his PhD at IRISA under the supervision of Rémi Gribonval and defended his thesis in October 2017. From 2017 to 2019, he was a postdoctoral researcher at École Normale Supérieure, working with Gabriel Peyré on the CFM–ENS “Laplace” Chair in Data Science, before joining CNRS as a full-time researcher in 2019.

His work has been recognized with the Best Student Paper Award at SPARS 2017 and the SIAM Activity Group on Imaging Science Early Career Prize in 2022. He was awarded an ERC Starting Grant in 2024 for the project MALAGA (Reinventing the Theory of Machine Learning on Large Graphs), which began in 2025.

Country:France

Affiliation:CNRS

Research interests:Machine learning and Signal processing on graphs, GNNs, Random graphs, Dimensionality reduction and Sparsity