Abstract
ATLAS: Agentic Trajectory Learning for Alignment and Security

Detects behavioral misalignment in AI agents at the trajectory level rather than the language level: instead of inspecting what an agent says, ATLAS inspects the sequence of actions it takes, encoded under the 6A Trace Schema — a semantic layer above OpenTelemetry with provenance markers separating declared from behavior-inferred intent. A 7–14B LLM backbone pretrained on 6A-encoded trajectory corpora, with fine-tuned detection heads, scores deviation in real time, attributes the decisive step, and forecasts failure before it lands. The view below renders Dallas's career as one such trajectory — actions tagged under the 5A ontology that 6A grew out of, scrubbable by year, filterable by ambit.

ADVISOR · John Hale (Chair)  ·  COMMITTEE · Tyler Moore · Brett McKinney · Roger Wainwright

Publications

  1. First author A Tandem Approach to CPS Threat Modeling ICISSP 2026 · 2026
  2. First author LLM-Assisted CPSTRIDE Threat Modeling for Critical Water Infrastructure ICCWS 2026 · 2026
  3. First author CPSTRIDE: A Threat Modeling Framework for Cyber-Physical Systems CRITIS 2025 · 2025
  4. Contributing author Industries of the Future Institutes: A New Model for American Science & Technology Leadership PCAST · U.S. Dept of Energy · 2021

Talks

  1. 2026-04
    Vibe Engineering with Claude Code
    BSidesOK · Tulsa, OK

    Live talk delivered through a custom local FastAPI + reveal.js stack with a co-presenting Claude Code session that listens to the room via Whisper.cpp and edits the slide deck in real time.

  2. 2025-09
    Oklahom.ai
  3. TEDx
    TEDx