Computational Topology For Data Analysis

Speaker: Javier Perera-Lago, University of Seville

Abstract: In this talk, Javier will provide an introduction to Topological Data Analysis (TDA), a branch of mathematics that applies concepts from computational topology to analyze and understand the shape of data. He will explain the basics of two of the most widely used techniques in TDA: the Mapper algorithm and persistent homology. Finally, he will demonstrate how these tools can be applied in data analysis and artificial intelligence, and how they can support the REXASI-PRO project in developing sustainable and safe solutions.

Biography: Javier Perera-Lago has a double degree in mathematics and statistics and a master's degree in mathematics from the University of Seville, where he is now doing his PhD. He studies computational topology and its applications to data analysis and artificial intelligence. Javier is visiting IDSIA for the whole month of October to work on the application of topological data analysis to multi-agent systems in the context of REXASI-PRO, a Horizon Europe project developing trustworthy AI to help mobility-impaired people. Join us to kick-off discussions on topological data analysis and AI!

Host: Prof. Rizzoli Andrea Emilio