Axelle Méric
Stable and Reproducible Change-Point Detection in Time Series through Multi-Scale and Consensus-Based Methods
Dauphine–PSL · Madalina Olteanu & Rebecca Killick · academic PhD
Research training
PhD supervision
Seven co-supervised PhD projects in statistics, learning and industry-facing research.
Ongoing PhDs
Yassine Ghariani
Modeling Non-Stationary Time Series in Energy Markets: Operator Learning and Conditional Density Estimation
Dauphine–PSL / ENGIE · Madalina Olteanu · CIFRE
Léo Saci
Guided Clustering of Irregular and Heterogeneous Multivariate Time Series for Unsupervised System Alignment and Latent Event Recovery
Dauphine–PSL / Murex · Madalina Olteanu · CIFRE
Aminata Ndiaye
Conditional Density Estimation and Counterfactual Inference
Dauphine–PSL / Renault · Madalina Olteanu · CIFRE
Completed PhDs
Bruno Belucci Teixeira
Learning from Tabular Data: Structural Regularization, from Small-Sample Neural Networks to High-Dimensional Clustering
Dauphine–PSL / BNP Paribas · Karim Lounici · CIFRE
Grégoire Pacreau
Operator Learning for Recommender Systems and Uncertainty Quantification
École polytechnique / Institut Polytechnique de Paris · Karim Lounici
Benjamin Riu
Comparing Joint and Marginal Distributions through Label Permutations for Regression and Conditional Density Estimation
École polytechnique / Institut Polytechnique de Paris · Karim Lounici
Ongoing thesis titles reflect the ANR dossier wording and may be updated to match final registered titles.