Profil personnel
Personal profile
He is a professor in the Department of Applied Mathematics at École Polytechnique, where he has been working since September 2013. His research is conducted at the Center for Applied Mathematics (CMAP), which he has had the privilege of directing since September 2025. He is a member of the SIMPAS team (Signal, IMage, Numerical Probabilities, and Statistical Learning). There, he works on data-related issues, using approaches from machine learning, artificial intelligence, statistics, and signal processing.
He has a strong interest in practical applications and in sharing knowledge through teaching. He is involved in both initial and continuing education. He is responsible for several courses offered by the School, including the MScT Data Science and Artificial Intelligence for Business, as well as continuing education programs (AI for Business and Leading with Data and AI) for Polytechnique Executive Education.
He also contributed to the creation of the M2 Data Science program at the Institut Polytechnique de Paris and managed the Applied Mathematics and Data Science PA for many years.
Intérêts de la recherche
His current research focuses primarily on two areas: health (particularly women's health) and reinforcement learning.
Empreinte digitale
- 1 Profils similaires
Collaborations et principaux domaines de recherche des cinq dernières années
Résultat de recherche
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Analyse automatisée de la cardiotocographie en intrapartum : état des lieux, controverses et perspectives
Ben M’Barek, I., Holmström, E., Ceccaldi, P. F., Michel, J., Vitrou, J., Le Pennec, E. & Stirnemann, J., 1 janv. 2026, (Accepté/En presse) Dans: Gynecologie Obstetrique Fertilite et Senologie.Résultats de recherche: Contribution à un journal › Article › Revue par des pairs
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DeepCTG® 2.0: Development and validation of a deep learning model to detect neonatal acidemia from cardiotocography during labor
Ben M'Barek, I., Jauvion, G., Merrer, J., Koskas, M., Sibony, O., Ceccaldi, P. F., Le Pennec, E. & Stirnemann, J., 1 janv. 2025, Dans: Computers in Biology and Medicine. 184, 109448.Résultats de recherche: Contribution à un journal › Article › Revue par des pairs
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Integration of clinical features in a computerized cardiotocography system to predict severe newborn acidemia
Menzhulina, E., Vitrou, J., Merrer, J., Holmstrom, E., Amara, I. A., Le Pennec, E., Stirnemann, J. & Ben M’ Barek, I., 1 avr. 2025, Dans: European Journal of Obstetrics and Gynecology and Reproductive Biology. 307, p. 78-83 6 p.Résultats de recherche: Contribution à un journal › Article › Revue par des pairs
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Wavelet-Based Multiscale Flow For Realistic Image Deformation in the Large Diffeomorphic Deformation Model Framework
Gaudfernau, F., Blondiaux, E., Allassonnière, S. & Le Pennec, E., 1 avr. 2025, Dans: Journal of Mathematical Imaging and Vision. 67, 2, 10.Résultats de recherche: Contribution à un journal › Article › Revue par des pairs
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Near-Optimal Distributionally Robust Reinforcement Learning with General Lp Norms
Clavier, P., Shi, L., Le Pennec, E., Mazumdar, E., Wierman, A. & Geist, M., 1 janv. 2024, Dans: Advances in Neural Information Processing Systems. 37Résultats de recherche: Contribution à un journal › Article de conférence › Revue par des pairs
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Progressive State Space Disaggregation for Infinite Horizon Dynamic Programming
Forghieri, O., Castel, H., Hyon, E. & Le Pennec, E., 30 mai 2024, Proceedings of the 34th International Conference on Automated Planning and Scheduling, ICAPS 2024. Bernardini, S. & Muise, C. (eds.). Association for the Advancement of Artificial Intelligence, p. 221-229 9 p. (Proceedings International Conference on Automated Planning and Scheduling, ICAPS; Vol 34).Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collection › Contribution à une conférence › Revue par des pairs
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Towards Minimax Optimality of Model-based Robust Reinforcement Learning
Clavier, P., Le Pennec, E. & Geist, M., 1 janv. 2024, Dans: Proceedings of Machine Learning Research. 244, p. 820-855 36 p.Résultats de recherche: Contribution à un journal › Article de conférence › Revue par des pairs
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A multiscale algorithm for computing realistic image transformations – Application to the modelling of fetal brain growth
Gaudfernau, F., Allassonière, S. & Le Pennec, E., 1 janv. 2023, Medical Imaging 2023: Image Processing. Colliot, O. & Isgum, I. (eds.). SPIE, 1246404. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol 12464).Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collection › Contribution à une conférence › Revue par des pairs
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Development and clinical validation of real-time artificial intelligence diagnostic companion for fetal ultrasound examination
Stirnemann, J. J., Besson, R., Spaggiari, E., Rojo, S., Loge, F., Peyro-Saint-Paul, H., Allassonniere, S., Le Pennec, E., Hutchinson, C., Sebire, N. & Ville, Y., 1 sept. 2023, Dans: Ultrasound in Obstetrics and Gynecology. 62, 3, p. 353-360 8 p.Résultats de recherche: Contribution à un journal › Article › Revue par des pairs
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Input uncertainty propagation through trained neural networks
Monchot, P., Coquelin, L., Petit, S. J., Marmin, S., Le Pennec, E. & Fischer, N., 1 janv. 2023, Dans: Proceedings of Machine Learning Research. 202, p. 25140-25173 34 p.Résultats de recherche: Contribution à un journal › Article de conférence › Revue par des pairs