I am a computer scientist, applied mathematician, and a Ph.D. candidate at the University of Minnesota, Department of Computer Science. My research is focused on the application of ideas from topology and category theory to a range of multi-disciplinary problems. I am interested in the general class of problems regarding the characterization of computations that exist on or are parameterized by networks. Of particular interest are neural networks, knowledge networks, and other complex systems. My hope is that by applying mathematical tools with the proper level of abstraction, we can better probe representations embedded in complex networks, allowing for more structured data science, explainable AI, and further insight into the structure of knowledge.

My CV is available here.

news

Sep 28, 2020 Sheaf Neural Networks, work with Jakob Hansen, was accepted as a Spotlight presentation in the NeuRIPS 2020 Workshop on TDA-in-ML.
Sep 28, 2020 Our work on the topological structure of scientific knowledge networks is on the arXiv.
Aug 12, 2020 I gave a talk on PCA, Dimensionality, and NSD at the NSD mini conference. Slides here.
Feb 16, 2020 I will be presenting a poster on Identifying the Intrinsic Dimensionality of FFA in Natural Scenes using the NSD dataset at VSS2020.
Dec 7, 2019 I will be giving a talk on path homologies of feedforward neural networks and presenting a poster at ICMLA2019.