Research

_{At JSM 2025 in Nashville}

I love working on statistical problems that have direct links to applied problems. In my dissertation work, I work on methods in Small Area Estimation that are relied upon to allocate billions of dollars for the largest government programs in the US.

Some of my interests include:

• Bayesian Methods
• Small Area Estimation
• Areal/Spatial Data Modeling
• Using Machine Learning Techniques to Improve Statistical Models

I am co-advised by Zehang Li and Paul Parker.

Updates:

• My first dissertation project was published in the The Journal of the Royal Statistical Society, Series A (JRSS-A)!
  • Spatially Selected and Dependent Random Effects for Small Area Estimation with Application to Rent Burden
  • Access the publication here.
• Presented the paper at JSM 2024 in Portland (link to slides).
• This paper won the Wray Jackson Smith Award from the Government Statistics Section of the ASA