Teaching

CYB-4203/6203 — Secure & Trustworthy AI

A graduate / undergraduate course at the University of Tulsa, delivered Spring 2026. Built from scratch.

Topics span ethics, harms & misuse, AI regulation & legal context, biology / neuroscience / psychology connections, privacy, bias, transparency, explainability, AI/ML attack vectors, testing, evaluation, red-teaming, and industry applications.

The course uses LLM-assisted instructional methods and a self-hosted course site. Assignments require students to use Claude Code, Codex, or Gemini CLI. The final project is a six-team red-team engagement against a multi-agent OpenClaw harness running on RunPod — students attack, document, and report.

Autonomous Systems Workforce Program — Summer 2026 to present

Team Lead for LLM, repo, and infrastructure on TU’s Autonomous Systems Workforce Program. Co-authoring Artificial Intelligence: Principles & Practices, a high-school AI course aligned to Oklahoma CS Standards and NIST NICE, with a course site and a Fall 2026 classroom pilot in partnership with Tulsa Innovation Labs and the U.S. EDA. Co-delivered a three-day workshop for K-12 educators: AI in the K-12 Classroom and Navigating AI Hype and Doom.

Red Teaming AI Systems — Spring 2027

A new Red Teaming AI Systems course at TU, built from scratch. Originally planned for Fall 2026; now slated for Spring 2027.

AIML@TU

I co-founded the AI/ML Club at the University of Tulsa and now serve as its Outreach Director, after two years as Graduate President. We run workshops, talks, a vibe-coding series, three Multi-Club Mashups, and the inaugural Hurricane Hackathon.