Biography
I am a Visiting Assistant Professor of Statistics at Reed College. Generally, my research interests are in small area estimation, hierarchical Bayesian modeling, applications of statistical methods to forestry and natural resources problems, and statistical software development. More specifically, my research focuses on implementing model-based statistical methods for small area estimation of forest attributes, and developing methodologies for formal assessment of those estimators.
I have a passion for teaching data science and statistics, and for mentoring undergraduate students on research projects. I have had the great pleasure of co-directing and mentoring students in the Undergraduate Forestry Data Science Lab during summers at Harvard University and at Bucknell University.
I passionately believe in the benefits of statistical software for teaching, learning, and research. I developed the R package gglm in order to allow statistics and data science educators to introduce linear model diagnostic plots while staying within tidyverse-syntax and using ggplot2. Further, in order to extend the reach and impact of my research projects, I have developed R packages the implement the introduced methodology, such as saeczi and kbaabb. I also maintain an R package with my collaborators from the U.S. Forest Service, FIESTA, which is used for both internally and externally for forest inventory estimation projects and research.
Education
Michigan State University | East Lansing, MI, USA
PhD in Forestry | Expected 2026
M.S. in Statistics | 2025
Reed College | Portland, OR, USA
B.A. in Mathematics (concentration Statistics) | 2021