Robbie User

Advise scientists at a federal research laboratory on novel applications of Bayesian survival (time-to-event) analysis and modeling approaches for small, data-scarce experimental studies.

Serve as quantitative researcher on joint projects with the Kansas Water Institute, the Kansas Department of Agriculture, and SAS. Co-developed a spatio-temporal modeling framework for optimizing Best Management Practice funding to control nonpoint source pollution.

Advise graduate researchers on experimental design, data analysis, and interpretation of results.

Led workshops on solving problems with messy data and presenting technical ideas as a data scientist.

Designed and built multi-agent LLM networks that automate and accelerate market research for a regional marketing firm, significantly improving efficiency of market research operations.

Taught and supported four undergraduate and graduate statistics courses over four semesters, including Regression and Analysis of Variance (STAT 705) and Biometrics I and II. Built coursework and lectured on probability, regression, and distribution theory.

Overhauled the company's data management practices and applied data analytics to identify and streamline inefficient internal workflows, and spearheaded website development.

Assessed company processes and recommended where AI could improve efficiency. Trained employees on AI tools and built AI-assisted training modules for Low-Income Housing Tax Credit (LIHTC) property management.

Pursuing a PhD in Statistics with an expected graduation in Spring 2028.

Completed a Master of Science in Statistics and Data Science in August 2026.

Earned a Bachelor of Science in Microbiology in May 2021.