Education
Education
Academic training
The foundation of how I teach. Graduate and undergraduate degrees in statistics and mathematics, with coursework spanning the full range of topics my students encounter and extending well beyond them.
M.S. Statistics: Advanced Methods & Data Analysis
Rigorous graduate training in modern statistical methodology, theory, and computation. My coursework covered the full theoretical inference sequence, regression methods for both independent and dependent (correlated) data, the design and analysis of experiments, categorical data analysis, and statistical computing, alongside an applied biostatistics sequence and a capstone in applied statistics. This is the foundation behind the predictive modeling, simulation, and uncertainty quantification in my research, carried out in R and Python.
The University of Washington ranks #3 among U.S. public universities, with its Department of Statistics ranking #6 in the nation (U.S. News, 2026).
Selected coursework
B.S. Mathematics
A mathematics degree with a specialization in statistics, built on a deeply proof-based core: the full calculus sequence, linear algebra, differential equations, real analysis, numerical methods, and proof writing, paired with statistics coursework in probability, statistical theory, regression and linear models, categorical data analysis, and statistical computing.
Mathematics & statistics
Sciences & engineering
I began university as an engineering major, which gave me a broad STEM foundation across the physical and life sciences and engineering, in addition to my mathematics and statistics core. That range helps me connect ideas across subjects and meet students wherever their coursework sits.