Topology holds the key to explain many relevant phenomena in the real world; the perspective of looking at foundational information, such as connectivity, can result in stable summaries of a data set. But enough about that pitch, you probably agree that topology rocks if you found your way here!

This page contains some of my talks, presentations, and links to other things I am organising, such as machine learning outreach programmes. Feel free to use any illustrations from the slides—as long as you attribute me as the original creator. If you want to get the original sources of the graphics, just reach out to me.

I try to record my talks as much as possible, so be sure to check out my YouTube channel for more content!

(Also feel free to visit the rest of this website for more academic content; most of my publications deal with topological concepts one way or the other.)

Talks

• Two Households, Both Alike in Dignity: Geometry and Topology in Machine Learning
  August 2024; slides for an invited talk at the 4th Annual Centre for Topological Data Analysis Conference, University of Oxford

• Levelling Up Your Scientific Writing
  February 2024; slides for a meta-talk on how to improve your writing skills

• Emerging Topics in AI: Geometry and Topology
  December 2023; slides for a keynote talk at the Bridging Disciplines Workshop 2023, University of Mainz

• Digital Emancipation: Creating Your Own Research Website
  July 2023; slides for an outreach talk that aims to improve the visibility of early-career researchers

• What’s in a Graph?
  May 2023; slides for a talk in the ‘I Can’t Believe It’s Not Better’ monthly seminar series. This talk is meant to give a sweeping overview of the field of graph learning, while also pointing out a couple of issues and troubling trends.

• Geometrical–Topological Loss Terms for Shape Reconstruction
  September 2022; slides for a talk at the Workshop ‘Topology of Data in Rome’, Tor Vergata University Rome

• The Memory of Persistence
  July 2022; slides for a Keynote at the ICML 2022 Workshop on Topology, Algebra, an Geometry in Machine Learning

• A Good Scale is Hard To Find: Shape Analysis Using Topology
  June 2022; slides for a talk at the LipiTUM research group, Technical University Munich. A recording is available on my YouTube channel.

• Topology-Based Graph Learning
  March 2022; slides for the Dagstuhl Seminar ‘Graph Embeddings: Theory meets Practice ‘

• Topological Representation Learning: A Differentiable Perspective
  February 2022; slides for ‘TDA Week’ at Kyoto University

• Zoom and Enhance: Towards Multi-Scale Representations in the Life Sciences
  February 2022; slides for the Chalmers ‘AI4Science’ Seminar

• Topology-Based Graph Representation Learning
  August 2021; slides for the Oxford ML Summer School ‘Unconference’ track. A recording is available on my YouTube channel.

• Learning Topology-Based Graph Representations
  July 2021; slides for the MSU TDA Seminar.

• Recent Advances in Topology-Based Graph Classification
  April 2021; slides for the IMSI Workshop on Topological Data Analysis. This is one of my signature talks, updated to include some recent work. A recording is available on my YouTube channel.

• A Bestiary of Autoencoders
  March 2021; slides for the Digital Campus of D-BSSE.

• Topological Representation Learning for Structured and Unstructured Data
  February 2021; slides for an invited talk at the DataShape seminar of Inria Sophia Antipolis.
  This PDF is best viewed with a PDF viewer that supports animations, such as Adobe Acrobat Reader DC

• Recent Advances in Topology-Based Graph Classification
  December 2020; slides for an invited talk in the Applied Mathematics Seminar of Yale University. This is similar to the talk I gave in October, but there are some pointers towards more recent work of TDA in a metric space setting.

• A Primer in Topological Data Analysis (Lecture 1, Lecture 2)
  November 2020; slides for a guest lecture in the course Geometric Data Analysis of Prof. Guy Wolf at Université de Montréal.
  The second lecture PDF is best viewed with a PDF viewer that supports animations, such as Adobe Acrobat Reader DC

• Advances in Topology-Based Graph Classification
  October 2020; slides for an invited talk at the University of Oxford Data Science Seminar and at Michael Bronstein’s research group at Twitter.

• Topology-Based Representation Learning
  July 2020; slides for an invited talk at the research group of Prof. Kathryn Hess Bellwald at EPFL
  This PDF is best viewed with a PDF viewer that supports animations, such as Adobe Acrobat Reader DC

• The Many Faces of Manifolds
  February 2020; slides for the intra-departmental seminar at D-BSSE in Basel

• Introduction to Topology-Based Graph Classification
  January 2020; slides for an invited talk at the AI & Topology session of the Applied Machine Learning Days in Lausanne

• Perspectives in Persistent Homology
  September 2019; slides for a keynote talk at the Applications of Topological Data Analysis Workshop co-located with ECMLPKDD 2019 in Würzburg

• Introduction to Machine Learning for Biology
  June 2019; workshop slides for the 2019 D-BSSE Retreat in Muttenz

• An Enchiridion for Topological Data Analysis
  June 2018; talk at Basel Postdoc Retreat in Klosters

• Statistically significant shapelet mining for biomedical time series
  June 2018; invited talk in the graduate seminar of Prof. Filip Sadlo

• Shakespearean Social Network Analysis using Topological Methods
  July 2016; lecture in the graduate seminar of Prof. Filip Sadlo

• An introduction to persistent homology
  May 2016; public lecture for the SIAM Chapter Heidelberg

• Ein Bild sagt mehr als tausend Worte: Graphische Darstellungen komplexer Daten
  May 2016; public lecture for the ‘Akademische Mittagspause 2016’ lecture series

• Persistent homology for multivariate data visualization
  Februrary 2016; invited talk at Sorbonne Universités UPMC in the research group by Dr. Julien Tierny

• Aspects of human perception
  June 2015; lecture in a course of Dr. Hubert Mara

• Die Poincaré-Vermutung
  May 2014; lecture in a course at ‘Privatgymnasium St. Leon-Rot’, a private high school

• Aspekte menschlicher Wahrnehmung
  January 2014; lecture in a course of Dr. Hubert Mara

• Weniger Klartext reden!
  September 2013; public lecture for the ‘Science Academy’

• Oh my god, it’s full of data–A biased & incomplete introduction to visualization
  April 2013; lecture in the fellows seminar of my graduate school

• Die Poincaré-Vermutung
  September 2012; public lecture for the ‘Science Academy’

• Applied algebraic topology
  July 2011; informal presentation I gave as a precursor to my Ph.D. project

Tutorials

• ‘Topological Data Analysis for Machine Learning’ at ECML PKDD 2020
  Topological Machine Learning is a nascent domain of machine learning research that employ concepts from (applied) topology to improve or analyse machine learning models. I gave a four-part tutorial on this topic for a general computer science audience that was not necessarily exposed to the mathematical background.

Workshops

• Second Workshop on ‘Geometrical and Topological Representation Learning’ at ICLR 2022
• First Workshop on ‘Geometrical and Topological Representation Learning’ at ICLR 2021
• ‘Topological Data Analysis and Beyond’ at NeurIPS 2020