Research
Geospatial methods, applications for statistics, and resources.
UF Smathers Libraries, University of Florida
August 2026 - Present
I am currently collaborating with geospatial librarians Dr. Javiera Rudolph and Joe Aufmuth to create extensive documentation of R, Python, and ArcGIS geospatial analysis workflows. We have created a variety of interactive code examples and tutorials using Quarto including tutorials on loading and storing data in R, data wrangling and the mathematical concepts of bias, spatial statistics, data mining, and generalized linear models. We then publish these documents to the UF Smathers Libraries catalog for other faculty and graduate students to use. In addition to extensive documentation, we have explored resources and robustness of extreme value analysis methods in geospatial applications such as long-distance migration in birds or extreme weather events.
Tracking pitch distributions, n-gram melodies, and rhythms across centuries in symbolic European folk music.
University of Florida USP, Department of Statistics
April 2026 - Present
I received the Undergraduate Scholars Program grant from the Center for Undergraduate Research at UF to study computational methods regarding folk music. In particular, I am working within a field called computational ethnomusicology, which focuses on the statistical and computational methods used in studying historical music and its significance across cultures and ethnicities. This project focuses on European folk music from the 13th to 20th centuries. My research primarily focuses on different methods for classifying and analyzing the presence of melodic and rhythmic phrasing in symbolic folk music, usually involving n-gram analysis. I am collaborating on this project with Dr. Elizabeth Johnson in the statistics department and Dr. Imani Mosley in the music department. We hope to publish our findings in an academic journal and present a poster in spring, 2027.
Applications of bayesian machine learning in causal inference with randomized controlled trials.
Yale School of Public Health, BDSY program (NIH Funded)
Summer 2026
While at Yale for the summer, I worked with Dr. Fan Li and Dr. Bhramar Mukherjee in the Big Data Summer Immersion at Yale program. My team studied Acute Kidney Injury using advanced Bayesian statistical models such as Bayesian Additive Regression Trees on clinical data. We evaluated the assumptions needed for such models under the Neyman-Rubin Causal model, wrote R scripts to estimate causal effects, and evaluated the robustness of our results. We then presented these results at the Yale Summer Research Symposium with both a 30 minute oral presentation and a posterboard. Additionally, this program focused on a variety of graduate-level statistics with an emphasis on data equity and biostatistics. In particular, my team explored violations to the causal framework and identified areas in need of future research in Bayesian model development.
Stereoscopic Parameters, Space Resection Algorithms, and CloudCompare plugins.
University of Florida School of Forests, Fisheries, and Geomatics
August 2025 - June 2026
I have worked with Dr. Ben Wilkinson and PhD students conducting research in computer vision, image registration, and spatial resections. We produced deliverables to non-profits involved in coastal research on the Florida Gulf. I also wrote a custom algorithm to replicate a computer vision space resection, which takes as input $n$ object points in $\mathbb{R}^3$ and $n$ matching image points in $\mathbb{R}^2$ and returns a solution for $X,Y,Z,\omega$ (Roll), $\phi$ (Pitch), and $\kappa$ (Yaw): the extrinsic camera parameters. Additionally, I created an experimental design for a research project focused on optimizing parameters for stereoscopic photogrammetry. And, using CloudCompare compiled from source, I worked on developing plugins in C++ and Python aimed at optimizing and automating various photogrammetric workflows.
Take-all Disease in Wheat: Exploring large dataset management and analysis at Rothamsted Institute, England.
University of Florida in England, Department of Statistics
Summer 2025
I studied under UF professors Dr. Beth Johnson and Dr. David Holmes, as well as researchers at the Rothamsted Institute in England. We examined associations between different wheat cultivars, environmental conditions, and the presence of take-all- a prominent and devastating crop disease. Specifically, my team focused on variable selection methods and data visualization. We also used well-established theoretical statistical methods like multiple regression and stratification to systematically chart changes in wheat disease over time. This project culminated in a presentation to the data scientists and biologists at Rothamsted, who continue to work with UF students to analyze their agricultural experiments. I greatly enjoyed the challenge and unique experience of working with complicated, agricultural data alongside prominent data scientists, professors, and colleagues.
Educational Tools for Biochemical Modeling, University of Florida College of Education
January 2025 - May 2025
I worked under Dr. Ken Crippen in the UF College of Education to design and evaluate educational material focused on biochemical molecular modeling and simulations. We utilized 3d modeling tools alongside PhD students in Education to create a lesson plan targeted at high-achieving high school students. The curriculum involved state-of-the-art modeling tools recently developed at UF and other collaborating institutions. My contribution to this project included a detailed lesson plan which provided a hands-on, guided walkthrough of new modeling tools accessible to them, as well as demonstrations of some basic high school level chemistry concepts. Additionally, I met with researchers several times throughout the project timeline to discuss learning objectives, educational philosophy, and applied biochemistry topics to improve upon these resources. My passion for teaching led me to this opportunity, and I enjoyed being able to create educational resources on my own, something which I hope to continue as I become more involved in academia and education.