Research Projects & Experience

Graduate Research

Interests:
Measurement bias, algorithmic fairness, measurement theory in machine learning, machine learning applications in behavioral sciences

Experience:
National Science Foundation Graduate Research Fellow
L.L. Thurstone Psychometric Lab
Aug 2021 - Present

Sample Projects:
Treatments of ordinal measures in machine learning
A simulation study assessing the predictive performance associated with various treatments of ordinal outcome variables in machine learning.

Undergraduate Research

Experience:
Undergraduate Research Assistant
Learning Analytics and Measurement in Behavioral Sciences Lab
Sep 2017 - May 2020

Undergraduate Research Assistant
Performance Analytics Team of Notre Dame Athletics
May 2018 - May 2020

Sample Projects:
Prediction of differential performance between AP exam scores and class grades
A machine learning application on student assessment data to understand why a student may rank differently on a high-stakes standardized test versus a teacher-assigned class grade.

Text analysis on Academy Awards acceptance speeches - actors vs. actresses
A text analysis project to quantitatively compare transcripts of Academy Award acceptance speeches given by actors and actresses to investigate speech style differences across gender. The project involves web scraping, data cleaning, and several text analytic techniques including sentiment analysis, structural topic modeling, and part-of-speech tagging, all done in R.

North Carolina Public Schools School Report Card - adapted
A data visualization project on an adaptation of the NC Public Schools School Report Card. The final product is an interactive report in Tableau, with the source data cleaned in R.

Cost-sensitive neural networks for classifying mushrooms
A cost-sensitive neural network analysis for detecting poisonous vs. edible mushrooms and experimentation with varying misclassification costs. The network is built with PyTorch.