Matt Piekenbrock

Github Scholar Email: matt (dot) piekenbrock (at) gmail

I’m a computer scientist with research interests in geometric and topological data analysis, unsupervised learning, algorithm design, and scientific computing. More information about my background and experience can be found on my online CV and my Github profile.

I’m currently a (transferred) PhD student at Khoury College of Computer Sciences, Northeastern University (NEU); prior to transferring, I completed 2 years of graduate coursework from the Computational Mathematics, Science, and Engineering Department (CMSE) at Michigan State University. I hold both B.S. and M.S. degrees in C.S. from Wright State University.

My research has been supported by various sources, including the NSF, NASA, DARPA, the Center for Survelliance Research, and a Ginther Fellowship, among others.


  • I’ve been invited to give a contributed talk AIM-AMS special session on Applied Topology Beyond Persistence Diagrams
  • Short paper accepted at Computational Persistence 2023. I am scheduled to give a 30-minute contributed talk on my research on spectral rank relaxations around September 25th
  • I’ve been invited to chair and give a contributed talk at the Third Graduate Student Conference: Geometry and Topology meet Data Analysis and Machine Learning
  • I’ve been invited to give a contributed talk to the AMS Spring special session on Topological Persistence: Theory, Algorithms, and Applications (IV) @ Georgia Tech, Atlanta (03/19/2023)
  • I’ll be attending the Jount Mathematics Meetings (JMM) in in Boston, Massachusetts (01/05/2023)
  • I’ll be attending the 2022 AMS Mathematical Research Communities (MRC) retreat on Data Science at the crossroads of Analysis, Geometry, and Topology