Over the last two decades, research in persistent homology and its applications in topological data analysis has developed from a conceptual mathematical framework into a powerful tool whose use has become commonplace in fields as diverse as machine learning and differential geometry. Modern approaches to understanding the geometric and topological structure of point clouds make extensive use of these methods, necessitating a good command of the relevant tools developed in the persistent framework.
The aim of this school is to bring together researchers working in the field of computational topology, particularly in persistence theory and its applications in Topological Data Analysis (TDA), to work together on topics in the field. By fostering collaboration at the intersection of mathematics, data science, and the natural sciences, the school will prepare students at the PhD or postdoc level with a solid background in topology or persistent homology to tackle open problems in TDA. There will be a selection of contributed talks.
Our Global Mobility Fellowships provide participation opportunities for selected researchers and PhD students from countries of the Global South in the Special Topic Schools of the Hausdorff School for Mathematics. For more information, please visit our website.
The deadline for the application for participation is May 31st, 2026.
Lecture series by:
- Kathryn Hess Bellwald (École Polytechnique Fédérale de Lausanne)
- Magnus Bakke Botnan (Vrije Universiteit Amsterdam)
- Yasuaki Hiraoka (Kyoto University)
- David Loiseaux (Inria Saclay)
Scientific Organizers:
- Ulrich Bauer (TU Munich)
- Felix Boes (University of Bonn)
- Benedikt Kolbe (University of Bonn)
- Vanessa Robins (Australian National University)