Richard J. Young, Ph.D.

In the classroom

What I teach

I teach IS 335 Business Analytics to undergraduates, plus graduate courses in big data and AI in healthcare, and I advise Data Analytics capstone projects. Most of my students are not planning to become data scientists, and that is fine. My goal is that you leave able to look at a spreadsheet, a dashboard, or a model's output and ask the right skeptical question.

Outside the classroom

What I work on

I am also a Senior AI Research Scientist at UnitedHealth Group, where I build and evaluate AI systems used in clinical and operational settings. My research asks a narrow question with large consequences: how do AI models fail when you push on them?

That has meant adversarial testing of frontier language models, checking whether a model's stated reasoning matches how it actually reached its answer, auditing fairness in AI used for emergency-department triage, and building retrieval systems for clinical medicine. I publish the benchmarks and datasets openly so others can check the results.

Earlier work sits in computational biology and neuroscience, including papers in Nucleic Acids Research and Alzheimer's & Dementia. I co-chair the UnitedHealth Group Enterprise IRB, which reviews human-subjects research across the enterprise.

This is why the examples in class are not hypothetical. When we talk about a model being confidently wrong, or a dashboard hiding the thing that matters, it is usually something I ran into that month. Selected publications and a fuller description of each thread are on the research page.