I am an AI Researcher and Applied Engineer (PhD Candidate, ABD) bridging high-stakes federal missions and advanced technical implementation. Currently the Director of AI at USAI, I architect secure, human-aligned GenAI ecosystems and lead research into Security Normal Form (SNF) for canonicalizing large-scale security telemetry.

• Mission: To treat AI safety as an empirical science, using rigorous measurement to understand how models impact human wellbeing.
• Current Focus: Building Agentic Workflows, Graph RAG, and automated cATO patterns for federal GenAI adoption.
• Philosophy: "Understanding the 'latent' traits of ourselves and others is the key to breaking down barriers and fostering empathy."

My research at the University of Tennessee focuses on Personality-Aware AI and the PRISM Protocol. I treat agents as latent-state dynamical systems, evaluating how trait-based conditioning impacts behavior, alignment, and coordination.

An experimentation hub for evaluating agent behavior across five rigorous research pillars. It repurposes narrative grounding into actionable personality evidence.

• PRISM Protocol: A trait-state protocol for agents involving State Vectors ($P_S$), Trajectories ($\Delta P_S$), and Valence ($).
• Key Metrics: Psychometric Agreement (PA), Trait Discriminability (TD), Drift Magnitude (DM), and Collapse Time (CT).
• Status: Under Review (ACM TIST, 2026).

Applied research at USAI to canonicalize heterogeneous security telemetry at 1 Million alerts daily using GPU-accelerated density clustering on Kubernetes/Kubeflow.

• Vision-to-Graph: Automating the extraction of nodes/edges from security diagrams for automated ATO analysis.

A machine-readable taxonomy of 44 psychometric models.

• Standardization: Mapping models into a 5-part lexical schema (Factor, Adjective, Synonym, Verb, Noun).
• Artifact: Personality-Trait-Models — Foundational library for optimizing recommender systems.

• Impact: Deployed the VA’s first GenAI production system on Microsoft Azure Government (MAG), scaling to 1.5M+ daily records for mental health detection.
• Innovation: Surfaces Social Determinants of Mental Health (SDoH) through closed-loop AI observation.

A complete graduate-level curriculum (COSC 650, UTK) covering the practical applications of Generative AI.

• Modules: RAG Foundations, Agentic Workflows, and Constitutional AI.
• Resources: 400+ curated research papers and 50+ hands-on notebooks.

• VA Innovation Award (2024): For the CLEVER Pipeline & AI-Assistant deployment.
• .34M AVIN Innovation Grant: Integrating personality models into autonomous systems.
• M ENCQOR 5G Grant: AI/ML behavioral integration in connected corridors.
• NSA Scientific Achievement Award: Critical mission research in boundary defense.

• LinkedIn
• X