Invited Talks
2024
2024, August 8th. Invited talk at The Battle of the Metrics Community Event at the Cognitive Computational Neuroscience (CCN2024). MIT, Boston. Riemannian Geometry of Neural Representations in Natural and Artificial Intelligence.
2024, July 27th. Keynote at the ICML GRaM Workshop (Geometry-grounded Representation Learning and Generative Modeling). Geometric Intelligence.
2024, July 15th. Keynote at the Eresfjord School of Mathematical Methods in Computational Neuroscience. Hierarchical Equivariance in Artificial and Natural Brains.
2024, June 18th. Keynote at the CVPR Equivision Workshop on Equivariance in Vision. Hierarchical Equivariance in Artificial and Natural Brains.
2024, June 17th. MIT DHIVE Program. Digital Twins and the Role of AI in Advancing Women’s Brain Health.
2024, May 28th. UC Riverside Seminar. Robust G-Invariance in G-Equivariant Networks.
2024, May 22nd. Distinguished Speaker for the Annual Tutte Lecture. Geometric Computations in Natural and Artificial Brains.
2024, May 13th. Ann S. Bowers Women’s Brain Health Seminar. Digital Twins and the Role of AI in Advancing Women’s Brain Health.
2024, February 15th. Lie Theory for Vision Grant Colloquium at UC Berkeley Redwood Center for Theoretical Neuroscience. Robust G-Invariance in G-Equivariant Networks.
2024, February 13th. Caltech’s Math & Machine Learning Seminar. Robust G-Invariance in G-Equivariant Networks.
2024, February 9th. UCSB Physics Graduate Seminar. From theoretical physics to geometric intelligence.
2024, January 25th. Workshop of Graph Neural Networks for the Sciences. A survey of message passing topological neural networks.
2023
2023, December 8th. Workshop Spatial Data Science in an Age of Scientific Disruption. Keynote: Geometric Artificial Intelligence.
2023, November 30th. Harvard University, Department of Applied Mathematics. The Differential Geometry of Neural Manifolds.
2023, November 28th. University of North Carolina at Chapel Hill, Applied Physical Sciences Colloquium. Architectures of Topological Deep Learning: A Survey of Topological Neural Networks.
2023, November 16th. UC Noyce Initiative's Launch of the Ann Bower's Women Brain Health Initiative. Artificial Intelligence for Brain Image Analysis: What Do We Know About the Female Brain?
2023, October 6th. Workshop on Multiphysics Measurements and Bayesian Methods. A Survey of Topological Neural Networks.
2023, August 17th. MIT Summer School of Geometry. Architectures of Topological Deep Learning: A Survey of Topological Neural Networks.
2023, July 18th - Eresfjord School in Mathematical Methods in Neuroscience. Geometry and Topology of Neural Manifolds.
2023, June 19th - University of British Columbia. Center for Brain Health. Architectures of Topological Deep Learning: A Survey of Topological Neural Networks.
2023, June 18th - CVPR Workshop on Computational Cameras and Displays. Deep Generative Modeling for Volume Reconstruction in Cryogenic Electron Microscopy: A Survey.
2023, June 18th - CVPR Workshop on Topology, Algebra and Geometry. (Keynote). Architectures of Topological Deep Learning: A Survey of Topological Neural Networks.
2023, June 8th - Flatiron Institute, Simons Foundation. CryoEM Summer Workshop. Deep Generative Modeling for Volume Reconstruction in Cryo-Electron Microscopy.
2023, May 31st - UCLA Applied Mathematics Seminar - Coding Differential Geometry for Machine Learning.
2023, May 15th - Ann S. Bowers Women’s Brain Health Initiative. Internal Kickoff. Geometric Deep Learning for Neurodegeneration.
2023, April 19th - IEEE Central Coast Event Talk - Geometric Learning for Shape Analysis from Bioimaging Data.
2023, April 17th - UCSB ECE Summit. Advancing Biomedicine with AI for Shape Analysis.
2023, April 15th - UCSB WISE Panels. Women in Science & Engineering: Academic Careers.
2023, February 17th - UCSB Differential Geometry Seminar. Geomstats: coding differential geometry for machine learning.
2023, February 17th - UCSB Physics Graduate Seminar. Riemannian Geometry: From General Relativity to Biomedical Imaging.
2023, January 31st - Data Science Initiative @ SISSA - Bioshape Analysis with Geometric Learning.
2023, January 13th - UCSB Machine Learning Seminar. Geometric Machine Learning.
2022
2022, November 16th - UCSB ECE Graduate Seminar. Geometric Machine Learning.
2022, November 14th - UCLA ECE Seminar. Shape Learning in Biomedical Imaging.
2022, October 11th - INRIA Saclay, Seminar of the SODA / MIND (previously Parietal) teams. Geomstats: A Python Package for Geometry in Machine Learning.
2022, October 10th - Workshop Geometry, Topology in Statistics and Data Science of the Thematic Program of Institut Poincaré. Geomstats: A Python package for Geometry in Machine Learning.
2022, September 29th - SIAM Conference on Mathematics of Data Science. Mini Symposium of Statistics and Machine Learning in Topological and Geometric Data Analysis. Geomstats: A Python package for Differential Geometry in Machine Learning.
2022, September 7th - Geo2Int (Geometry and Geometric Integration) Workshop. Geomstats: A Python package for Differential Geometry in Machine Learning.
2022, June 20th - Keynote for the CVPR Deep Learning for Geometric Computing (DLGC) workshop. Shape Learning in Biomedical Imaging.
2022, June 8th - University of Washington, eScience Institute Semina and Geomstats Workshop. Geometric Learning for Shape Analysis in Bioimaging.
2022, June 1st - Sage Math conference. Geomstats: A Python package for Differential Geometry in Machine Learning.
2022, May 6th - Pacific Institute for the Mathematical Sciences (PIMS) workshop. CompSPI: Open-Source Software for Biological Imaging – Best Coding Practices.
2022, May 2nd - John Hopkins University Center for Imaging Science Workshop. Geometric Learning for Shape Analysis from Bioimaging.
2022, April 13th - UCSB, Cryo-EM FIB Forum. Deep Generative Models for Molecular Reconstructions in Cryo-Electron Microscopy.
2022, March 11th - Psych & Brain Sciences Department Seminar. Brain Shapes.
2022, March 9th - Computer Science Summit, UC Santa Barbara. Biomedical Shape Analysis with Geometric Learning.
2022, February 17th - Invited Lecture, University of British Columbia, Canada. Deep Generative Models for Molecular Reconstructions in Cryo-Electron Microscopy.
2022, January 26th - Materials Research Outreach Symposium, UC Santa Barbara. Shape Learning: From Images to Scientific Insights.
2022, January 25th - Physics Department Colloquium, UC Santa Barbara. Riemannian Geometry: From General Relativity to Biomedical Imaging.
Previous
2021, December 14th - Mathematical Engineering Seminar, UC Louvain. Riemannian Geometry in Statistics and Machine Learning.
2021, December 13th - Séminaire MINES Paristech - PSL Research University. Geomstats: a Package for Riemannian Geometry in Statistics and Machine Learning.
2021, November 19th - Physics Graduate Students Seminar, UC Santa Barbara. From General Relativity to Biomedical Imaging.
2021, November 5th - Toronto Geometry Colloquium. Exploring the Geometries of Life. (Video).
2021, October 27th - Banff International Research Station's workshop BIRS-CMO Geometry & Learning from Data. Geomstats: a Python package for Geometry & Learning from Data (Video).
2021, October 13th - Probability Seminar, UC Santa Barbara. Geometric Statistics for Biological Shape Analysis.
2021, July 14th - 63rd ISI World Statistics Congress 2021. Submanifold learning with Riemannian Variational Autoencoders.
2021, July - Stanford University. Invited Lecture. Probability distributions on manifolds.
2021, February 17th - UC Davis, Seminar on Inference for Dynamical Systems. Geomstats: a Python package for Riemannian geometry in dynamical systems.
2020, March 30th - Lausanne, Switzerland. Workshop on Statistics for Indirectly Measured Functional Data. 3D shape reconstruction with pose estimation: what is the right metric?
2020, March 23th - Oberwolfach, Germany. Workshop on Optimization on Riemannian manifolds. Geomstats: a python package for Riemannian geometry in machine learning.
2020, November 15th - Math Bio Seminar of the University of British Columbia. Geometric Statistics for shape analysis of bioimaging data.
2020, October 1st - Stanford University, USA. Probability distributions on a Riemannian manifold.
2020, March 10th - Harvard Medical School, USA. Advancing cancer research with analysis of bioimaging data.
2020, February 19th - UC Santa Barbara, USA. Seminar of Electrical and Computer Engineering. Advancing medical research with shape analysis of bioimaging data.
2020, February 13th - Stanford SLAC, USA. Seminar of Articial Intelligence. Shape learning.
2020, January 23th - Georgia Tech, USA. Seminar of Mathematics & Biology. Shape analysis of bioimaging data.
2020, January 8th - UC Davis, USA. Statistics Seminar. Statistical shape analysis for bioimaging data.
2019, September 5th - Toulouse, France. Workshop on Geometric Statistics. Learning weighted submanifolds using geometric variational autoencoders.
2019, August 29th - Toulouse, France. Geometric Science of Information Conference. Geomstats: a python package for Riemannian geometry in machine learning.
2019, June 18th - Salt Lake City, USA. Math in the Desert Workshop. Submanifold learning with variational autoencoders: Application to brain manifold learning.
2019, March 16th - San Francisco, USA. Molecular Med Tri-Conference & Bio-IT West. Building a Computational Model of the Human Anatomy using Medical Images.
2019, February 20th - Berkeley, USA. Seminar of UC Berkeley. Statistics on Shape Data: Correcting an Asymptotic Bias in Template Shape Estimation.
2018, July 15th - Stockholm, Sweden. International Conference of Machine Learning (ICML), Workshop Geometry in Machine Learning (GiMLi). Geometric Statistics: Learning from Medical Images?
2018, May 19th - Baltimore, USA. Seminar of John Hopkins University, Center of Imaging Science. Geometric Statistics for Image Analysis.
2018, January 28th - Oberwolfach, Germany. Meeting of the Mathematisches Forschungsinstitut Oberwolfach.Geometric Statistics for Computational Anatomy in the Session on Statistics for Data with Geometric Structures.
2017, December 16th - London, UK. 10th International Conference on Computational and Methodological Statistics (CMStatistics 2017). Geometric Statistics for Computational Anatomy in the Session on Statistics for data with geometric structure.
2017, November 16th - Cambridge, UK. Shape analysis and computational anatomy workshop. Template shape estimation: correcting an asymptotic bias.
2017, December 20th - Goettingen, Germany. Goettingen Statistics Seminar. Open questions in Geometric Statistics.
2017, December 13th - London, UK. BioMedIA Seminar of the Department of Computing, Imperial College London.Geometric Statistics for medical image computing.
2017, November 29th - Kingston, Canada. Seminar at Queen's Hospital. AI for Diagnostic Radiology.
2017, September 23rd - Orlando, USA. American Mathematical Society (AMS) Sectional Meeting. Estimation on manifolds: synchronization of rotations for cryo-electron microscopy in the Special Session on Mathematics of Biomolecules: Discrete, Algebraic, and Topological.
2016, June 7th - Stanford, USA. Stanford Statistics Seminar. Template shape estimation in Computational Anatomy.
2015, November 2nd - Montpellier, France. Statistics Seminar of Université de Montpellier. Statistical properties of the Fréchet mean in quotient spaces. Applications to Computational Anatomy.
2015, February 19th - Vienna, Austria. International Workshop on Infinite-Dimensional Riemannian Geometry with Applications to Image Matching and Shape Analysis. Erwin Schroedinger International Institute for Mathematics and Physics. Noise Effects on Quotient Spaces M/G.