Guillaume Principato

PhD Student in Applied Mathematics at Université Paris-Saclay.

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Office 3A3,

Building 307

Orsay, France 91405

I’m a CIFRE PhD student in statistics and machine learning at Laboratoire de Mathématiques d’Orsay (LMO), in collaboration with Electricity of France (EDF) and INRIA, as part of the Défi EDF-INRIA. My research is supervised by Jean-Michel Poggi, Gilles Stoltz, Yvenn Amara-Ouali, Yannig Goude, and Bachir Hamrouche.

My research is centered on uncertainty quantification and predictive modeling, with applications in areas such as energy forecasting, including EV charging and load consumption. I am particularly interested in conformal prediction, time series forecasting, and hierarchical forecasting methods.

News

May 31, 2026 Our article Conformal Prediction for Hierarchical Data has been published at TMLR
Mar 24, 2026 I presented Adaptive Conformal Inference through the Lens of Blackwell Approachability at the Statistic and Optimisation Seminar in the Mathematics Institute of Toulouse (IMT)
Jan 16, 2026 I presented Conformal Prediction for Hierarchical Data at the Califrais Seminar at their office in Paris
Dec 16, 2025 I presented Conformal Prediction for Hierarchical Data at the LIPS Seminar in Centre Borelli
Dec 05, 2025 I attended the 2025 ECAS-SFDS winter school Towards Reliable Machine Learning. Thanks to all the speakers for the great courses!

Selected publications

Blackwell’s Approachability for Sequential Conformal Inference (2025)

Guillaume Principato, Gilles Stoltz