Research Link to heading
At the moment, I am interested in understanding applications of different curvature measures on finite, undirected graphs. The hope is to bring ideas from differential geometry and computational topology and adapt them to discrete structures (e.g. graphs) and use them to bolster graph topics in graph learning. In this first work, we target graph generative modeling workflows by providing a more expressive, foundational comparison method for distributions of graphs. This could have serious implications in a number of fields including molecular generation and drug development. I am also interested in pioneering new curvature + TDA methods for research questions in environmental science (particularily climate change) and medicine.
I will try to keep this page updated to reflect what projects I am thinking about/working on at the moment. If you’d like to chat or have ideas for a collaboration, please send me an email!