Presentations and Publications
Homology of Colored Graphs: A Framework for Type-Aware Network Topology
Student Research Conference — March 2026
College of Computational, Mathematical, and Physical Sciences, Brigham Young University (Provo, Utah).
We introduced a hypothesis testing framework for topological network analysis, for testing for independence between a graph partition and its homology.
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Signature Projects
Persistent Homology of Archaeological Similarity Networks (June 2026 - Present)
This paper introduces persistent homology, a Topological Data Analysis (TDA) technique, as an alternative to traditional network analysis for studying Archaeological Similarity Networks (ASNs). Applied to ceramic data from the Chaco region (1050-1100 AD), this method identifies structural gaps and dense clusters of cultural similarity, demonstrating its robustness against missing data and arbitrary thresholding in assessing cultural transmission boundaries.
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Predicting Multiple Sclerosis using Functional Logistic Regression (April 2026)
This presentation explores the application of Functional Logistic Regression to predict Multiple Sclerosis (MS) using spatial dynamics data from Diffusion Tensor Imaging (DTI). Specifically, the project evaluates the use of Derivative Principal Component Analysis (DPCA) on Fractional Anisotropy (FA) measurements from the Corpus Callosum (CCA) and Right Corticospinal Tract (RCST) to improve classification accuracy over non-derivative models.
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Network Dynamical Systems Simulator (December 2025)
Architected a Python simulation framework using NumPy and NetworkX for discrete dynamical systems on graphs. The project models non-linear node-state evolution across complex network topologies and features optimized state-update algorithms that utilize SciPy sparse matrix operations, reducing computational complexity from O(|V|²) to O(|E|).
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Competitive Chess Network Analysis (November 2025)
An analysis of historical chess match-ups (Lumbra’s Gigabase) between players rated 1800+ using network science principles. The project explores node importance through various centrality measures (degree, eigenvector, betweenness) and identifies community structures, demonstrating that competitive chess networks exhibit real-world characteristics like scale-free-like degree distributions, small-world properties, and an onion core-periphery structure.
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Socioeconomic Inequality Statistical Analysis (July 2024)
R-markdown analysis project using R: Uncovered trends in poverty and race in relation to crime rates using official US Census data. Showcased abilities in hypothesis testing, linear regression, ANOVA, model validation, API data extraction, exploratory data analysis, and data visualization (ggplot).
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Stock Price Tracking Application (June 2024)
Python Application: implemented and automated ETL process to retrieve data from Yahoo Finance API via yfinance python module, appropriately transforming resulting data with pandas, and loading resulting data frame into a Plotly Dash app graphically and tabularly: Showcase abilities with Python, Dash, Plotly, Pandas, yfinance, HTML, and CSS.