Stanley Durrleman

Biography

Training

• Habilitation to direct research (HDR), Université Pierre and Marie Curie (2018)
• Doctorate in applied mathematics, Université Nice-Sophia Antipolis (2010) - summa cum laude
• Graduate of the Ecole Supérieure des Télécommunications, Paris (2006)
• Master's degree in Mathematics, Vision and Learning (MVA), Ecole Normale Supérieure de Paris Saclay (2005)
• Graduate of Ecole Polytechnique (2004)

Professional experience

• Holder of a research chair at the PRAIRIE interdisciplinary institute for artificial intelligence (2019 -)
• Co-leader of the ARAMIS team at the Brain Institute (ICM) (2019 -)
• Director and founder of the Neuroinformatics Centre at the Brain Institute (2017 - 2021)
• INRIA researcher at the Brain Institute, on secondment from the Corps des Mines (2011-)
• Post-doctorate at the Scientific Computing and Imaging Institute, University of Utah, USA (2010 - 2011)
• Doctoral student in the Inria Asclepios team under the supervision of Nicholas Ayache (2007-2010)

Research work

Modelling and predicting the progression of neurodegenerative diseases - Integrating multimodal data (imaging, clinical) into computational models - Predicting the progression of a neurodegenerative disease - Designing decision support tools for patient monitoring or inclusion in clinical trials

Publications

• AD Course Map charts Alzheimer’s disease progression, I Koval, A Bône, M Louis, …, S Durrleman, Scientific Reports, Vol 11 (1), p 1-16, 2021
• Learning the spatiotemporal variability in longitudinal shape data sets, A Bône, O Colliot, S Durrleman, International Journal of Computer Vision, Vol 128(12), p 2873-2896, 2020
• Spatiotemporal propagation of the cortical atrophy during the course of Alzheimer’s Disease: Population and individual patterns, I. Koval, J.-B. Schiratti, A. Routier, M. Bacci, O. Colliot, S. Allassonnière, S. Durrleman, Frontiers in Neurology, Vol 9, p 235, 2018
• A Bayesian mixed-effects model to learn trajectories of changes from repeated manifold-valued observations, J.-B. Schiratti, S. Allassonnière, O. Colliot, S. Durrleman, Journal of Machine Learning Research, 18(133):1−33, 2017
• Morphometry of anatomical shape complexes with dense deformations and sparse parameters, S. Durrleman, M. Prastawa, N. Charon, J. R. Korenberg, S. Joshi, G. Gerig, A. Trouvé, NeuroImage, 101(1):35-49, 2014