Research

Louisiana State University

My work lives in three connected places — the structure of graphs, the application of machine learning, and the teaching of mathematics.

Graph Theory

I work in structural and extremal graph theory: counting substructures such as cycles in planar triangulations, and labeling graphs over abelian groups. The recurring question is how local constraints force global structure.

extremal planar triangulations Γ-harmonious labeling

Applied ML

I apply machine learning to real-world problems where labeled data is scarce — from semi-supervised regression in healthcare to predicting body composition from 3D optical imaging.

semi-supervised p-Laplacian healthcare

Math Education

I care about making mathematics reachable: open and accessible resources, problem-driven learning, and writing that turns hard ideas into intuitions. Much of my notebook lives here.

open education exposition outreach