Greg Henselman

Greg Henselman
Graduate Student  

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Researh interests: Cellular matroid theory, computational topology, discrete optimization, topological data analysis


I am a fifth year PhD student interested in cellular sheaves, matroids, and applications.


My research focuses on the algebraic properties of combinatorial spaces arising in topological data analysis, as understood from categorical and matroid-theoretic perspectives. Current projects include Morse-theoretic algorithms for sheaf (co)homology computation with singular restriction maps, memory-efficient methods for computational persistent homology, and applications in random matrix theory and biological networks. I have an abiding philosophical interest in the role of cellular matroids in computational topology; beyond producing beautiful mathematics, I believe these have great potential to enrich our understanding of combinatorial data science (for the curious, a paper linked below gives some reasons why). If you'd like to talk about these or any other topics in computational topology, feel free to reach out. My contact information can be found above!


  1. Greg Henselman (2015) CV.. Attach:HenselmanCV.pdf. (BibTeX)

  2. Greg Henselman and Paweł Dłotko (2014) Combinatorial Invariants of Multidimensional Topological Network Data. IEEE Global Signal & Information Processing Symposium, Dec. Attach:CombinatorialInvariants.pdf | Attach:Appendix.pdf | Attach:Poster. (BibTeX)

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