Transfer Learning
and TSFM

Mathilde Mougeot

Professor of Data Science & Holder of the Industrial Data Analytics and Machine Learning Chair
ENS Paris-Saclay / Centre Borelli / ENSIIE

Mathilde is a researcher in applied mathematics and data science. Her work focuses on statistical learning, predictive modelling, model aggregation, and transfer learning, with strong ties to industrial applications.

Véronique Maume-Deschamps

Professor of Applied Mathematics & Director of the Institut Camille Jordan (ICJ)
Université Claude Bernard Lyon 1

Véronique Maume-Deschamps is Professor of Applied Mathematics at Université Claude Bernard Lyon 1 and Director of the Institut Camille Jordan. Her research spans probability, statistics, and uncertainty quantification, with a particular focus on stochastic dependence modelling, extreme value theory, statistical learning, and risk analysis, motivated by applications in insurance, finance, and environmental sciences.

Vladimir R. Kostić

Associate Professor of Applied Mathematics & Senior Researcher
University of Novi Sad & Italian Institute of Technology

Vladimir R. Kostić is an Associate Professor of Applied Mathematics at the University of Novi Sad and a Senior Researcher at the Italian Institute of Technology. His research lies at the intersection of computational mathematics, numerical linear algebra, statistics, and machine learning, with a particular focus on stochastic processes, dynamical systems, and the development of computational methods for AI for Science.

Rémi Flamary

Professor of Applied Mathematics
École Polytechnique

Rémi Flamary is Professor of Applied Mathematics at École Polytechnique and a member of the CMAP laboratory. His research lies at the intersection of machine learning, optimization, and optimal transport, with a particular focus on domain adaptation, graph learning, representation learning, and statistical signal processing, motivated by applications in biomedical engineering, remote sensing, energy, climate, and astronomy.

Shifeng Xie

PhD student
Université Paris Cité

Shifeng is a PhD student in Themis Palpanas's group at Université Paris Cité, after studying engineering at Télécom Paris and Institut Polytechnique de Paris. His research focuses on time series foundation models and agentic systems for forecasting, reasoning, and decision-making.

Tahar Nabil

AI Scientist
EDF R&D

Tahar holds a PhD from Télécom Paris in signal processing. At EDF R&D, he works on time series foundation models and generative AI for industrial process design.

Adrien Petralia

AI Scientist
Mistral AI

Adrien holds a PhD from Université Paris-Cité on deep learning for time series in the energy sector, spanning signal separation, foundation models, and generative modelling for load disaggregation.

Etienne Le Naour

AI Scientist
EDF R&D

Etienne holds a PhD from Sorbonne Université, in collaboration with EDF R&D, on neural representation learning for time series. He now builds foundation models for time series with a focus on forecasting and imputation.

Raphael Nedellec

Data Science Manager
Decathlon

Raphael's research focuses on forecasting and calibrated quantile regression using semi-parametric additive models, with widely-used contributions such as the qgam and mgcViz R packages. He now leads data science work at Decathlon.

Roberto Stanzione

Post-Doc student
INRIA (Valda)

Roberto completed his PhD at the University of Salerno, working on relaxed functional dependencies, concept drift detection in machine learning systems, and federated learning. He is now a post-doc in the Valda team at Inria.