I gave a talk at PyCon DE & PyData 2025 introducing what topological data analysis is, primarily aimed at data scientists working with Python.

Links: abstract, slides

You can find my two tutorials about Voronoi diagrams and Delaunay tessellations made for AATRN on YouTube. Those classical constructions form a basis for many ideas used in TDA. The first tutorial summarizes what the objects are, the second one explains how a Delaunay tessellation can be computed efficiently.

The visualization I made for the first video is available at Wolfram Demonstrations Project.

One of the main projects I worked on during my PhD is a theoretical background and an implementation of algorithms for "chromatic TDA": a generalization of the standard TDA pipeline for extracting information from point clouds to the setting where the points have colors—e.g., positions of biological cells in a tissue sample, with each point colored red if it is a cancer cell, blue if it is an immune cell, and green if it is an endothelial cell.

I gave an introductory talk to the topic aimed at an audience familiar with the basics of TDA at the AATRN online seminar, which can be found on YouTube.