Teaching philosophy

Statistics you can actually run

Our teaching pairs sound statistical reasoning with hands-on, reproducible computing. Students learn to design experiments, analyze real agricultural data, and write code they can reuse in their own research — building the quantitative and programming skills that modern plant breeding and crop science demand.

Courses

Courses taught

Graduate courses in statistics and statistical computing for the agricultural sciences.

AGST 5014 Experimental Design — University of Arkansas Spring 2023, 2025, 2026
AGST 5713 Applied Regression Analysis for Agricultural Sciences — University of Arkansas Fall 2023
AGST 5023 Principles of Experimentation — University of Arkansas Fall 2022, Spring 2024
CPSC 441 Introduction to R Programming — University of Illinois Urbana-Champaign Fall 2020
Mentoring

Mentoring at a glance

Advising students and researchers across statistics, genetics, and computer science.

2
Postdoctoral fellows
5
Master's students
5
Undergraduate students
15
Advisory committees

Meet the people behind the work on our Team page.

Prospective students

Interested in graduate study in agricultural statistics, quantitative genetics, or data science for plant breeding? Reach out to discuss opportunities.

Contact us