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Xavier Pennec
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Position
- 3IA Côte d'Azur Chair holder on Geometric statistics and geometric subspace learning.
- Senior Research Scientist (Directeur de Recherche) at Inria since 2007.
- Previously: Research Scientist at INRIA (1998-2007) & Post-doctoral associate at MIT (1997).
Education
- Habilitation à diriger des recherches (HDR), University of Nice-Sophia Antipolis, FR, 2006.
- PhD from the Ecole Polytechnique, Palaiseau, FR, 1996, with highest honors.
- Master's degree, Ecole Politechnique and Ecole Normale supérieure, Paris, FR, 1993, with highest honors.
- Engineer Degree, Ecole Polytechnique, Palaiseau, FR, 1992.
Research interests
My research interest is at the intersection of statistics, differential geometry, computer science and medicine.
I am particularly interested in the mathematics involved in computational
anatomy: geometric statistics involve statistical computing on Riemannian manifolds and other
geometric structures (Lie groups, quotient spaces, stratified spaces, information geometry...). I contributed mathematically grounded methods and algorithms for medical image registration, statistics on shapes, and their translation to clinical research applications. I animated in particular the workshop Mathematical Foundations of Computational Anatomy from 2006 to 2019 and I co-edited in 2020 the first reference book on
Riemannian Geometric Statistics in Medical Image Analysis. In 2018, I was awarded the ERC Advanced Grant G-Statistics whose aim is to ground the mathematical foundations of geometric statistics and to exemplify their impact on selected applications in the life sciences.
Publications
Publication record:
Google scholar, ResearcherID,
Scopus,
ORCID,
DBLP,
Pubmed.
Complete bibliography:
On the Epione lab online bibliography or on the open archive hal system.
3rd book of Elsevier and MICCAI Society book series. This book aims at being a complete reference on statistics on Riemannian manifolds and more general nonlinear spaces with applications in medical image analysis. It provides an introduction to the core methodology with 5 chapters and 11 contributed chapters on state-of-the-art methods for applications.
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Nicolas Guigui, Nina Miolane and Xavier Pennec (2023), Foundations and Trends® in Machine Learning: Vol. 16: No. 3, pp 329-493.
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Contributions
Geometric Statistics
Manifold-valued image processing, DTI and metrics on SPD, PSD and correlation matrices
Medical image registration
Computational anatomy
Videos of some of my presentations
- Curvature effects in geometric statistics: empirical Fréchet mean and parallel transport accuracy
Video of a presentation at BIRS-CMO Workshop Geometry \& Learning from Data , Casa Mathematica de Oaxaca, Mexico, October 24-29, 2021.
- Geometric Statistics for Computational Anatomy. Beyond the mean value, beyond the Riemannian metric
Video of a presentation at IPAM's Pprogramm on Geometry and Learning from Data, Workshop on Geometric Processing, April 2, 2019, UCLA, Los-Angeles, USA.
- Sample Limited L_p Barycentric Subspaces Analysis on Constant Curvature Spaces
Video of a presentation at GSI'2017 - Geometric Science of Information, November 7-9, 2017, Mines ParisTech, France.
- Barycentric Subspaces and Affine Spans in Manifolds
Video of a presentation at GSI'2015 - Geometric Science of Information, October 28-30, 2015, Palaiseau, France.
- Geometric structures for statistics on shapes and deformations in computational anatomy
Video of a presentation at Medical Imaging Summer School MISS 2014, 28 July - 1Aug 2014 Favignana, Sicily.
- Demonology, or a short retrospective of Demons in medical image registration
Video of a presentation at Medical Imaging Summer School MISS 2014, 28 July - 1Aug 2014 Favignana, Sicily.
- Statistiques de formes et variétés anatomiques.
Video of the seminar at the College de France, May 13, 2014 (in French).
- Statistics on Deformations in Computational Anatomy: Geometric Structures and Topological Questions.
Video of the talk at the Topological Structures in Computational Biology workshop, IMA, Minneapolis, December 9, 2013.
- The stationary velocity field framework for modeling the progression of Alzheimer's disease.
Video of the lecture at the SCI Institute distinguished seminar series, Salt-Lake City, February 13, 2013.
- Statistical
Analysis of longitudinal deformations: Is there an alternative to the Riemannian setting?
Video of the lecture at
BIRS workshop on Geometry for Anatomy, Banff, August 31, 2011.
- L'anatomie algorithmique : une thématique émergente à l'intersection des sciences de l'information, des mathématiques et de la médecine.
Video of the lecture at the Colloquium "Le modèle et l'algorithme", INRIA Rocquencourt, March 3 2011.
- Statistical
Computing on Manifolds for Computational Anatomy.
Video of the lecture at Emerging
Trends in Visual Computing (ETVC'08), Palaiseau, November 18-20,
2008.
- A Riemannian Framework for Diffusion Tensor Analysis (8 Mb)
Slides of the presentation at the MICCAI'08 Workshop on Diffusion
MRI, NewYork, September 6, 2008.
- Statistical Computing on Manifolds.
Video of the talk at the Shape spaces workshop, IMA, Minneapolis, April 5, 2006.
Conferences and Workshops
- Medical Image Computing and Computer Assisted Interventions
(MICCAI)
conferences
- Information Processing in Medical Images (IPMI)
- Workshops on Mathematical Foundations of Computational Anatomy (MFCA):
2019,
2017,
2015,
2013,
2011,
2008,
2006.
- Workshops on Spatio-Temporal Image Analysis for Longitudinal and Time-Series Image Data (STIA):
2014,
2010.
- Topological and Geometrical Structure of Information, TGSI 2017, CIRM Luminy (FR).
- Geometric Science of Information (GSI):
2015,
2013.
Teaching:
Xavier
Pennec