I am a fourth-year Ph.D. candidate in Mathematics at Auburn University studying under Hal Schenck. I earned a B.S. in Mathematics with minors in History and Classics at the University of Kentucky. While at the University of Kentucky, I conducted research with the University of Kentucky Math Lab and also as part of the Multimodal Vision Research Laboratory.

My primary research interests lie in commutative algebra, algebraic geometry, and topological data analysis. However, I've been finding that a lot of side projects that interest me come from combinatorial optimization. A copy of my CV can be found here along with my contact information.



  1. Betti tables forcing failure of the Weak Lefschetz Property (with Hal Schenck). In: Springer INdAM series: The strong and weak Lefschetz properties (2023), to appear.

    PDF | Abstract
    We study the Artinian reduction \( A \) of a configuration of points \( X \subset \mathbb{P}^n \), and the relation of the geometry of \( X \) to Lefschetz properties of \( A \). Migliore initiated the study of this connection, with a particular focus on the Hilbert function of \( A \), and further results appear in work of Migliore–Miró-Roig–Nagel. Our specific focus is on Betti tables rather than Hilbert functions, and we prove that a certain type of Betti table forces the failure of the Weak Lefschetz Property (WLP). The corresponding Artinian algebras are typically not level, and the failure of WLP in these cases is not detected in terms of the Hilbert function.

  2. Surface modeling for airborne lidar (with Hunter Blanton and Nathan Jacobs). In: IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium. 2020, pp. 1110–1113. DOI: 10.1109/IGARSS39084.2020.9323522.

    PDF | Abstract
    Repeat-visit airborne lidar is a powerful tool for change detection in urban and rural environments. In this work, we present a learning-based approach that addresses one of the key challenges in comparing point cloud scans of the same region: handling geometric differences caused by varying sensor position. Our approach is to perform shape modeling through ray casting with a point cloud neural network. Recent work on learning-based shape modeling has been based on the assumption that an explicit surface representation is available, which is not the case for airborne lidar datasets. Our key insight is that by using a ray casting approach we can perform shape modeling directly with lidar measurements. We evaluate our method both quantitatively and qualitatively on learned surface accuracy and show that our method correctly predicts surface intersection even in sparse regions of the input cloud.


  1. Suturing the Severed Didactic Tetrahedron: Graph Theoretic Reflection to Foster Alignment in Coordinated Course (with Haile Gilroy and Melinda Lanius). Submitted.

    PDF | Abstract
    Despite online homework’s growing prevalence as a uniform component in coordinated mathematics courses, few studies have considered the connection, or lack thereof, between instructors of record and fixed online homework sets. In this mixed-methods study, we examined how 10 university mathematics educators working in a coordinated setting judged the quality of a sampling of online Calculus I homework assignments. Following an initial review of the homework sets, we introduced the educators to a novel instrument called the Course Alignment Analysis Tool (CAAT), which leverages graph theory to assess the alignment between the learning outcomes that an instructor feels should be prioritised and the learning outcomes most emphasised by an assignment or assessment. We analyzed the impact of engaging with the CAAT on participants’ consideration of uniform homework. We found that in- teracting with the CAAT affected coordinated instructors’ definitions of homework quality and that the CAAT is a promising professional development tool for novice instructors in particular.

  2. PDF | Abstract
    The connected sum construction, which takes as input Gorenstein rings and produces new Gorenstein rings, can be considered as an algebraic analogue for the topological construction having the same name. We determine the graded Betti numbers for connected sums of graded Artinian Gorenstein algebras. Along the way, we find the graded Betti numbers for fiber products of graded rings; an analogous result was obtained in the local case by Geller. We relate the connected sum construction to the doubling construction, which also produces Gorenstein rings. Specifically, we show that a connected sum of doublings is the doubling of a fiber product ring.

  3. PDF | Code | Abstract
    We introduce the MatrixSchubert package for the computer algebra system Macaulay2. This package has tools to construct and study matrix Schubert varieties and alternating sign matrix (ASM) varieties. The package also introduces tools for quickly computing homological invariants of such varieties, finding the components of an ASM variety, and checking if a union of matrix Schubert varieties is an ASM variety.

Graduate Research


Castelnuovo-Mumford Regularity

How complicated can generators and relations of a module be?


Lefschetz Properties

When does multiplication by a linear form have full rank in an Artinian algebra?


Topological Data Analysis

Use techniques from computational topology to analyze and exploit the shape of data.




A Macaulay2 package with functions for investigating ASM and matrix Schubert varieties.



A tool to help analyze course alignment.


Minimal Out-Neighborhoods

Python scripts for computing minimal out-neighborhoods (and some statistics) in the \( F \)-lattice.


Tropical Curves

Python scripts for visualizing tropical curves.

Undergraduate Research


Discrete Heisenberg Group

How well does Ehrhart theory translate to the noncommutative world?

flight route

Flight Route Estimation

How well can you estimate the path of a LiDAR sensor given a scan of the terrain?


twisted cubic

Visualizing Algebraic Surfaces

Cool 3D prints of objects popping up in math.


TA Assignments

Is there a nice algorithm to assign TAs to teaching assignments given a set of constraints and a list of preferences?


Generating Minecraft Worlds

Use techniques from deep learning combined with real world data to generate realistic worlds in Minecraft.

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