CV
A short, public summary appears below.
Position
University of Arkansas at Little Rock — faculty in mathematics and statistics; director of the Math Assistance Center.
Research interests
- Bias-robust Bayesian meta-analysis (RoBMA, model-averaged Bayes factors, selection models).
- Publication bias and evidential fragility in applied literatures.
- Nutrition and health evidence synthesis.
- Reproducible statistical workflows (R, Quarto, Git, simulation).
- Statistics education, including Bayesian intuition at the introductory level and responsible use of AI tools.
- Human-governed AI and curriculum infrastructure, including the Course Builder course-design harness.
See the Research page for current project descriptions.
Teaching and service
- Undergraduate and graduate teaching in mathematics and statistics.
- Director of the Math Assistance Center (MAC) at UA Little Rock.
- Maintainer of a ten-site public mathematics and statistics course-material portfolio.
- Developer of Course Builder, a human-governed course-design harness for AI-assisted curriculum work.
See the Teaching page for current courses.
Selected work
Preprint. Hester, M. Quantifying Evidential Rigor in Meta-Analytic Corpora: A Simulation-Characterized, Bias-Robust Bayesian Workflow with a Nutrition Case Study. Public preprint, arXiv:2606.01428.
- arXiv preprint: https://arxiv.org/abs/2606.01428
- Companion repository: https://github.com/matthewahester/evidential-audit-workflow
- Archived companion repository (Zenodo): https://doi.org/10.5281/zenodo.20467258
See the Research page for a plain-language description.
System development. Course Builder — a human-governed course-design harness (repo-native analytic exoskeleton) for AI-assisted curriculum work. Its current public demonstration layer is a ten-site course-material portfolio. See the Research page and the Teaching page.
Identifiers
- ORCID: 0009-0008-4242-4094
- GitHub: github.com/matthewahester