Frédéric Chazal (Inria-Datashape) ran a seminar at IRT SystemX, on June 20th on the following topic « Understanding the shape of data: a brief introduction to Topological Data Analysis ».
Abstract :
Topological Data Analysis (TDA) is a recent and fast growing field at the crossing of mathematics, computer science and statistics. It is mainly motivated by the idea that topology and geometry provide a powerful approaches to infer, analyze and exploit robust qualitative and quantitative information about the structure of data. With the emergence and development of persistent homology theory, computational topology and geometry have brought new efficient mathematical and computational tools to infer, analyze and exploit the topological and geometric structure of complex data. The goal of this talk is to provide a short introduction to TDA and persistent homology through the presentation of a few problems, results and concrete applications (sensors data analysis, graph structured data classification, etc…).
Biographie :
Frédéric Chazal is a Directeur de Recherche (senior researcher) at INRIA Saclay Ile-de-France since 2007. After a PhD in pure mathematics, he oriented his research to computational geometry and topology. He is now leading the DataShape team at INRIA, a group working on Topological Data Analysis (TDA), a recent fast growing field at the crossing of mathematics, statistics, machine learning and computer science. Frederic’s contributions to the field go from fundamental mathematical aspects to algorithmic and applied problems. He published more than 80 papers in major computer sciences conferences and mathematics journals, he co-authored 2 reference books and 3 patents. He is also an associate editor of 4 international journals: Discrete and Computational Geometry (Springer), SIAM Journal on Imaging Science, Graphical Models (Elsevier), Journal of Applied and Computational Topology (Springer).
During the last few years Frédéric has been heading several national and international research projects on geometric and topological methods in statistics and machine learning. He is also the scientific head of joint industrial research projects between Inria and several companies such as Fujitsu (TDA, Machine Learning and explainable AI) or the French SME Sysnav.
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