We are honored to be part of the Online workshop “Beyond TDA – Persistent topology and its applications in data sciences”.

Our Mattia Bergomi will speak about “Comparing Neural Networks via Generalized Persistence” on August 29th.

If you are bold enough to hear the world’s top mathematicians speaking of weird stuff you can find additional details here ?https://personal.ntu.edu.sg/XIAKELIN/TDAconf.html

Thanks also to Pietro Vertechi, the Researcher that is working with Mattia in our Laboratory.

Here’s the list of the Speakers:

  • Henry Adams, Colorado State University
  • Mattia G. Bergomi, Veos Digital, Milano
  • Ginestra Bianconi, Queen Mary University of London
  • Wojtek Chacholski, KTH Royal Institute of Technology
  • Stefania Ebli, EPFL
  • Herbert Edelsbrunner, IST Austria
  • ‪Massimo Ferri, University of Bologna
  • Patrizio Frosini, University of Bologna
  • Robert Ghrist, University of Pennsylvania
  • Jurgen Jost, Max Planck Institute
  • Claudia Landi, University of Modena and Reggio Emilia
  • Ran Levi, University of Aberdeen
  • Konstantin Mischaikow, Rutgers
  • Vasileios Maroulas, University of Tennessee
  • Facundo Mémoli, Ohio State University
  • Marian Mrozek, Jagiellonian University
  • Sayan Mukherjee, Duke University
  • Vidit Nanda, Oxford
  • Andreas Ott, Karlsruhe Institute of Technology (KIT)
  • Francesco Vaccarino, Politecnico di Torino
  • Guowei Wei, Michigan State University
  • Kelin Xia, Nanyang Technological University
  • ‪Hiraoka Yasuaki‬, Kyoto University


  • ‪Massimo Ferri‬ (UNIBO, Italy)
  • Vidit Nanda (Oxford, UK)
  • Jie Wu (HEBTU, China)
  • Guowei Wei (MSU, USA)
  • Kelin Xia (NTU, Singapore)

Topological data analysis (TDA) and TDA-based machine learning models have achieved great successes in various areas, such as materials, chemistry, biology, sensor networks, shape analysis, scientific visualization, dynamics systems, and image/text/video/audio/graph data analysis. Beyond TDA, various other geometric, topological and combinatorial models have been developed for representation, featurization, and analysis, including:

  • Multidimensional persistence, Zig-zag persistence, persistent local homology,
  • Reeb graph, discrete Morse theory, Conley index,
  • Path complex, Neighborhood complex, Dowker complex, hypergraph, and their persistent homology,
  • Geometric anomaly detection, discrete geometry, discrete exterior calculus, etc,
  • Spectral graph, spectral simplicial complex, spectral hypergraph, etc,
  • Graph/Hodge/Tarski Laplacian, p-Laplacian, topological Dirac,
  • Cellular Sheaves,
  • Persistent functions, persistent spectral, persistent Ricci curvature, etc.