The CUNY Data Science and Applied Topology Reading Group is joint between the Mathematics and Computer Science programmes. We meet Fridays 11.45 -- 12.45 in GC 3209. You can contact us at

Our plan is to primarily read and discuss seminal papers in data science, in applied topology and in topological data analysis. Each seminar one participant takes the responsibility to present a paper and prepare items for discussion. We expect occasionally to be able to invite external speakers.


Current schedule can be found here.

We will be sending out announcements through a mailing list; you can subscribe here.


  • Mikael Vejdemo-Johansson, Computer Science Programme, CUNY Graduate Center; Department of Mathematics, CUNY College of Staten Island
  • Azita Mayeli, Mathematics Programme, CUNY Graduate Center; Department of Mathematics, CUNY Queensborough Community College

Suggested papers

We have compiled a list of papers that might be interesting to present.


Fast estimation of recombination rates using topological data analysis

NOTA BENE: This talk will take place at 10am.

In this talk, I will describe recent work (joint with McGuirl, Miyagi, and Humphreys) that uses topological features to infer recombination rates from genomic data. Building on work of Camara, Levine, and Rabadan, we show that low-dimensional persistent homology contains a great deal of information about recombination. Perhaps most interestingly, we are able to explain the qualitative behavior of various topological features in terms of standard coalescent theory.


  • Data Science and Applied Topology Seminar
  • Reading list