Teaching, to me, includes formal instruction, day-to-day collaboration, and sustained mentoring. As a statistician working across disciplines, I try to help learners not only understand statistical methods, but also make good decisions about study design, modeling strategy, interpretation, communication, and reproducible analytic practice.
My teaching philosophy is that statistics education should build modeling, programming, and communication skills while also helping trainees avoid common analytic pitfalls, overstated conclusions, and avoidable misuse of methods.
Teaching Approach
For doctoral trainees
Methodological depth
For Ph.D. students interested in developing new statistical methods, I emphasize underlying theory, assumptions, derivations, and careful evaluation of model behavior.
For master's students
Applied analysis and communication
For students preparing for applied roles, I focus on hands-on analysis, coding, model selection, interpretation, and communicating results clearly to non-statistical audiences.
For collaborators
Practical statistical reasoning
For clinical and interdisciplinary collaborators, I emphasize study aims, method choice, interpretation, and the practical implications of analytic decisions.
Mentoring Experience
Since joining UNC in 2018, I have spent a substantial amount of time mentoring graduate students, junior biostatisticians, and research collaborators through active projects rather than only through isolated classroom examples.
- I have co-mentored Ph.D. students on dissertation work, helping shape research questions, analytic plans, programming workflows, and interpretation of results.
- I have guided trainees in preparing abstracts, posters, presentations, and manuscripts, with attention to both methodological rigor and clear communication.
- I regularly mentor junior biostatisticians through collaborative project work, helping them strengthen practical skills in data management, modeling strategy, reproducible coding, and client-facing scientific communication.
- I work closely with interdisciplinary teams to teach applied statistical thinking in context, including how to align study aims, data structure, analytic methods, and reporting.
Applied Teaching and Training
From 2021 to 2023, I also provided a short course for the Castillo Scholars program at UNC focused on study aims and the statistical methods best suited to address them. More broadly, I see mentoring as an important part of building independent researchers and thoughtful statistical collaborators who can contribute both technical expertise and sound scientific judgment.