Invitation to the 2nd Workshop on Topological Methods in Data Analysis

From 4th to 6th of October the Second Workshop on Topological Methods in Data Analysis will take place within the cluster of excellence STRUCTURES at Heidelberg University. The three-day workshop includes introductions into the powerful data analysis machinery of persistent homology, extensive tutorials on the versatile GUDHI library, and in particular features invited colloquial talks by well-known experts in the field, aiming for a broader audience. In addition, participants will have the opportunity to give a short presentation on their own TDA-related work. The workshop will take place online only.

Please find more information including the detailed schedule on the corresponding webpage and the attached information sheet.

We are pleased to announce that registration for the workshop is now open until October 1st. Registration proceeds via filling out this form. Shortly in advance to the workshop we will send around respective Zoom links.

Feel free to share this invitation with interested colleagues.

We are looking forward to your participation.

Do not hesitate to contact us in the case of questions.

Best regards
The organization committee consisting of Michael Bleher, Maximilian Schmahl, Daniel Spitz and Anna Wienhard

TDA Tenure Track, Oregon State University

Oregon State University invites applications for three full-time 9-month tenure-track Assistant Professor positions in Mathematics beginning September 16, 2022. The salary is commensurate with research and teaching experience.  Full consideration by November 1, 2021. The areas are: Mathematical Analysis (broadly defined), Applied Topology/Topological Data Analysis, and Probability with Applications in Data Science. 
Apply as follows: 
Assistant Professor:  Mathematical Analysis 
Assistant Professor:  Probability with Applications in Data Science
Assistant Professor:  Applied Topology – Topological Data Analysis
A copy of application must also be submitted on

ATMCS 10 – 20-24 June 2022, Oxford, UK

Dear All,
We announce with great pleasure that the 10th conference in the ATMCS series will be held in

Oxford, 20-24 June 2022

Conference webpage:

Invited Speakers:
Hélène Barcelo (Arizona State)
Saugata Basu (Purdue)
Ulrich Bauer (Technical University of Munich)
Andrew Blumberg (Columbia)
Peter Bubenik (Florida)
Gunnar Carlsson (Stanford)
Herbert Edelsbrunner (ISTA)
Alexander Grigor’yan (Bielefeld)
Facundo Memoli (Ohio State)
Elizabeth Munch (Michigan State)
Nina Otter (UCLA)
Leonid Polterovich (Tel Aviv)
Eric Sedgewick (De Paul)
Vin de Silva (Pomona College)
Katharine Turner (Australian National University)

In addition there will be contributed talks. A call for submission of abstracts for these talks and posters will follow.
Registration will open at the end of this year. Abstract submission deadline will be in early 2022.

Scientific Committee:Claudia Landi (Chair) (Università di Modena e Reggio Emilia)
Jacek Brodzki (University of Southampton)
Frédéric Chazal (INRIA)Brittany Fasy (Montana State University)Robert Ghrist (University of Pennsylvania)
Kathryn Hess (EPFL Lausanne)Yasu Hiraoka (Kyoto University)
Matthew Kahle (Ohio State University)
Primoz Skraba (Queen Mary, University of  London)
Schmuel Weinberger (University of Chicago)

We are pleased to report that Conference Proceedings of ATMCS10 will be published in conjunction with the Journal of Applied and Computational Topology (APCT). All those contributing to the conference will be invited to submit research and survey papers.

The conference is supported by the Centre for Topological Data Analysis.
Limited financial help will be available.

We look forward to welcoming you next year in Oxford!

Heather Harrington, Ulrike Tillmann and Vidit Nanda

Beyond TDA – Persistent Topology and its Applications in Data Sciences

Online workshop “Beyond TDA–Persistent topology and its applications in data sciences“, August 28-30, 2021  


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. 

The application of these models in data analysis can be generalized into four stages, i.e., data, topology, feature and learning. Essentially, data are transformed into certain topological representations. Intrinsic geometric/topological/combinatorial features are obtained from these representations and then further input into learning models. This workshop is supported by School of Physics and Mathematical Sciences, Nanyang Technological University, Singapore. 

Confirmed 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) 

More detailed information can be found here

Postdoc in Topological and Geometric Machine Learning for Marine Sustainability at University of Bergen

I’m happy to announce a 3-year postdoctorial position in topological and geometric machine learning for marine sustainability at the University of Bergen. The application deadline is on October 31. 

See for the full advertisement and application instructions.

Please contact Nello Blaser ( for any inquiries. 

AATRN: Second Interview Series

Hi all,

The Applied Algebraic Topology Research Network (AATRN) is hosting our second annual interview series:

Kathryn Hess interviewed by Peter Bubenik – Aug 11, 2021, 11am Eastern

Lisbeth Fajstrup interviewed by Martin Raussen – Sep 29, 2021, 11am Eastern

Robert Adler interviewed by Omer Bobrowski – Oct 20, 2021, 11am Eastern

Shmuel Weinberger interviewed by Katharine Turner – Feb 9, 2022, 11am Eastern

Robert Ghrist interviewed by Radmila Sazdanovic – Mar 9, 2022, 11am Eastern

For the zoom coordinates, please become an AATRN member at

or else email the AATRN directors at

You may find recordings of our prior interviews and other videos at

Best, Sara Kalisnik, Elchanan Solomon, Henry Adams

Postdoc, TDA for NLP, Düsseldorf

I am advertising a postdoc position at the intersection of topological data analysis, natural language processing and machine learning.

duration: 3 years
starting date: 1 October 2021
location: Heinrich Heine University Düsseldorf, Germany

Reflecting its interdisciplinary nature, the position is associated both with my group (Topology and Geometry) and with the research group of Prof. Milica Gasic (Dialogue Systems and Machine Learning). Prior experience in one or more of the named areas would be beneficial, but we are willing to consider outstanding candidates from other areas of mathematics.

The position will be paid at the TV-L E13 scale (see for more information). It comes with moderate teaching duties (2 times 90 minutes per week during teaching periods), which could be arranged to be of direct relevance for the intended research. Working knowledge of German would be beneficial but is not essential.

Applications and enquiries should be directed to by 30 August.

AATRN poster session

Dear applied topologists,

We (Henry, Antonio, Hanka, Teresa) are organizing open poster sessions via Zoom, with the intention of giving a platform to younger members of our community to showcase their work, as well as a place for everyone to present their most recent research results. Topics of interest will span the full range of applied and computational topology.

The webpage for the poster sessions is at

The sessions will be two hours long, and our first poster session will take place on Friday, October 8th, 2021 at 11am Eastern time. To submit a title and abstract, by September 24 please fill out the registration form at

Zoom coordinates and the website with the program will be sent out to the AATRN email list several days before each poster session.

Best wishes,
Henry Adams, Hana Dal Poz Kouřimská, Teresa Heiss, Antonio Rieser

CfP: Applications of Topological Data Analysis to Big Data

***** Call for Papers: Workshop on Applications of Topological Data Analysis to Big Data at IEEE BigData 2021 *****

Topological Data Analysis (TDA) is a growing area of research that focuses on studying the “shape” of data. Tools (such as persistent homology) from TDA have been successful in many application areas, including signal processing, computer vision, dynamical systems, and geospatial systems. This workshop will be a venue for researchers and practitioners of TDA to present innovative, state-of-the-art topological methods and novel applications of topological tools to big data.In this workshop, we invite submissions on recent applications of topological data analysis, with a focus on larger datasets. Topics include but are not limited to:

  • TDA applications to graphs, hypergraphs and networks
  • TDA applications in natural language processing
  • TDA applications to image and video analysis
  • TDA applications in dynamical systems and signal processing
  • Topological approaches to spatial and social systems
  • Topological approaches to machine learning

Important Dates

  • September 30, 2021: Due date for full workshop paper submission (11:59pm AoE)
  • November 1, 2021: Notification of paper acceptance to authors
  • November 20, 2021: Camera-ready version of accepted papers due
  • December 15–18, 2021: Workshop (one day in this date range)

This workshop will be held remotely. Additional information can be found at you,
Tegan Emerson (Pacific Northwest National Lab)
Mason A. Porter (University of California, Los Angeles)
Sarah Tymochko (Michigan State University & Pacific Northwest National Lab)
Wlodek Zadrozny (University of North Carolina at Charlotte)

SIAM Mini-Symposium : Sheaves and Homotopical Methods for Topological Data Analysis

Dear Applied Topologists,

It is our pleasure to invite you to the Mini-Symposium part of the SIAM-AG21 conference on Sheaves and Homotopical Methods for Topological Data Analysis, which will take place virtually on the 18th of August 2021.

If you are interested in participating, please register here before the 9th of August.

We look forward to see you there,

With best regards,

Nicolas Berkouk & François Petit


The theory of one-parameter persistence was developed in the early 2000’s as an attempt to define topological descriptors of datasets which are robust to noise – the so-called barcodes. Since then, it has led to important advances in diverse areas: material sciences, time series analysis, neuroscience, and neural networks, just to name a few. Although well understood, one-parameter persistence faces several limitations such as sensitivity to outliers or to the user’s choice of the function filtering the data. To overcome these shortcomings, the persistence community has introduced a generalization of the above construction: multi-parameter persistence. In this context, the algebraic theory of multi-parameter persistence becomes more complex, and the need for more refined techniques originating from algebraic topology and algebraic geometry more evident. In this symposium, the speakers will present their advances in the field of topological data analysis with a sheaf theoretical or homotopical perspective. They will emphasize the benefits of taking a more abstract point of view on theoretical as well as on applied problems and explain the challenges of computability raised by these approaches.

Organizers: Nicolas Berkouk & François Petit

Program (Eastern Time)

9:00-9:25 Sheaves As Data Structures, abstract , Robert W. Ghrist, University of Pennsylvania, U.S.

9:30-9:55 Computational Topology in Intersection Theory, abstract, Vidit Nanda, University of Oxford, United Kingdom; Martin Helmer, University of California, Berkeley, U.S.

10:00-10:25 Distances on Sheaves, abstract, François Petit, Sorbonne Universités, France; François Petit, Université de Paris, France

10:30-10:55 The Amplitude of An Abelian Category: Measures in Persistence Theory, abstract, Nina Otter, University of California, Los Angeles, U.S.

2:40-3:05 Multi Parameter Persistence on Crossroads of Homotopy Theory and Statistics, abstract, Wojciech Chacholski, KTH Royal Institute of Technology, Sweden

3:10-3:35 Homotopy Invariant Notions of Interleaving and Applications, abstract, Luis Scoccola, Michigan State University, U.S.

3:40-4:05 Persistent Homotopical Algebra, abstract, Grégory Ginot, Université Paris 13, France

4:10-4:35 The Truncated Interleaving Distance for Reeb Graphs, abstract, Elizabeth Munch, Michigan State University, U.S.