My research interests lie at the intersection of data science, machine learning, and education. Specifically, I focus on:

  • Applications of Data Science and Machine Learning in Educational Contexts
  • Quantitative Survey Methodologies for Educational Assessment
  • Large Language Models as a Tool for Educational Research
  • STEM Education Research


University of Michigan

Grasping Rationality and Instructional Practices (GRIP) Lab

As the lead graduate student researcher in the GRIP Lab, I contributed to the Geometry for Teachers (GeT) Support Project, focusing on:

  • Item-response theory analysis of MKT assessments.
  • Coding qualitative data and using machine learning models.
  • Developing and analyzing psychometric survey instruments.

College and Beyond II Project

In this project, I conducted statistical analyses to study the effects of liberal arts education on life outcomes, including:

  • Analyzing results from pilot surveys.
  • Providing readability statistics for essay responses.
  • Employing structural equation modeling.

Wolverine Pathways Curriculum Development Project

My role involved developing mathematics curriculum materials with a social justice orientation for a summer bridge program.