Selected publications from current research themes

• “Progressive State Space Disaggregation for Infinite Horizon Dynamic Programming” with O. Forghieri, H. Castel and E. Hyon, International Conference on Automated Planning and Scheduling (2024)
• “A multiscale algorithm for computing realistic image transformations - Application to the modelling of fetal brain growth” with F. Gaudfernau and S. Allassonnière. SPIE Medical Imaging (2023)
• “Input uncertainty propagation through trained neural networks” with P. Monchot, L. Coquelin, S. Petit, S. Marmin and N. Fischer. International Conference on Machine Learning (2023)
• “Causal and Interpretable Rules for Time Series Analysis” avec A. Dhaou, A. Bertoncello, S. Gourvénec, et J. Garnier. Knowledge Discovery and Data Mining (2021)
• " Intelligent Questionnaires Using Approximate Dynamic Programming" with F. Logé and H. Amadou-Boubacar, i-com (2021),
• “Learning from both experts and data” with R. Besson and S. Allassonnière, Entropy (2019),

Last Preprints

• “Towards Minimax Optimality of Model-based Robust Reinforcement Learning” with P. Clavier and M. Geist,
• “Wavelet-Based Multiscale Initial Flow For Improved Atlas Estimation in the Large Diffeomorphic Deformation Model Framework” with F. Gaudfernau, E. Blondiaux and S. Allassonière,
• “A Model-Based Reinforcement Learning Approach for a Rare Disease Diagnostic Task” with R. Besson, S. Allassonnière, J. Stirnemann, E. Spaggiari and A. Neuraz,

For more details, see the research page or the comprehensive list of publications

Current students

• Imane Ben M’Barek, PhD in co-supervision with Julien Stirnemann, 2023-, Prediction of neonatal hypoxia by automated analysis of cardiotocography during labor
• Orso Forghieri, PhD in co-supervision with Hind Castel and Emmanuel Hyon, 2022-, hierarchical reinforcement learning
• Inass Kamal, PhD in co-supervision with Angelo Pierangelo, 2022-,Multispectal Mueller polarimetric imaging
• Shadé Alao, PhD in co-supervision with Serge Cohen, 2022-, New statistical learning tools for imputation and prognosis in conservation science
• Pierre Clavier, PhD in co-supervision with Stéphanie Allassonnière, 2021-, Trajectory optimization to avoid medical wandering
• Amin Dhaou, PhD in co-supervision with Josselin Garnier, 2021-, CIFRE TotalEnergie, Causality and Time Series

Former students

• Fleur Gaudfernau, PhD in co-supervision with Stéphanie Allassonnière, 2020-2023, Diagnosis in IRM – Post Doc at Heka
• Paul Monchot, PhD, 2020-2023, CIFRE LNE, Supervised learning and sensibility – R&D at LNE
• Angie Pineda, Post Doc, 2018-2021, C’IL-LICO project, Health data – ENSAI
• Thomas Galtier, Post Doc, 2019-2020, HealthChain project, Data Valuation, Federated Learning
• Frédéric Logé-Munérel, PhD, 2017-2021, CIFRE Air Liquide, Planning and Reinforcement Learning – R&D at Sonio
• Rémi Besson, PhD in co-supervision with Stéphanie Allassonnière, 2016-2019, Rare Disease Diagnosis Optimization – CSO at Sonio
• Marco Brigham, Post Doc, 2017-2019, Morpheo project, EEG Analysis – CSO at Moonoia
• Esther Derman, Associate Researcher, 2016-2017, Model Based Histogram Clustering – moved to Israel, PhD at the Technion, post-doc at MILA
• Solenne Thivin, PhD, 2012-2015, CIFRE Thales Optronics, Detection on Complex Textures – professor in high school
• Lucie Montuelle, PhD, 2011-2014, Conditional Density Estimation – Engineer at EDF
• Joseph Salmon, PhD, 2007-2010, Estimator Aggregation – Full professor at Université de Montpellier