The path behind the work.
My path into engineering wasn't a straight line. I came to technology with a background that spans business, entrepreneurship, and cybersecurity, then found my lane where engineering and research meet. That path led me from graduate research at Norfolk State University to a competitively awarded IBM Master's Fellowship and, most recently, applied AI and cloud security research at the Air Force Research Laboratory. Each experience has reinforced the same thing: I do my best work when I'm learning, building, and solving problems that don't already have obvious answers.
Air Force Research Laboratory
HBCU/MI Summer Research Program — behavioral AI middleware (UNMASK) and secure cloud infrastructure (WHISPER).
Norfolk State University
Cybersecurity & AI Research Lab — graduate research on phishing, adversary behavior, and applied AI.
IBM Master's Fellowship
Competitively awarded fellowship supporting graduate AI/cybersecurity research at Norfolk State University.
Three disciplines. One engineering practice.
AI Engineering
I'm interested in what AI can understand beyond the immediate prompt—behavior, context, intent, and the patterns that emerge over time.
Cloud Security
I like building in the cloud with security designed in from the start: identity, least privilege, automation, and infrastructure that exists only as long as it needs to.
Research Engineering
Research gets interesting to me when I can turn the question into something real—write the code, test the idea, learn from the results, and improve it.
Two sides of intent.
One system explores how intent can be inferred from behavior. The other explores how sensitive intent can be protected from inference. Both became working engineering systems during my AFRL research.
Adversaries don't announce their intentions. What if AI could recognize the behavior that gives them away?
UNMASK explores concealed intent across multi-turn conversations by analyzing behavioral signals that become visible over time — not just what a user says in a single prompt.
How do you ask a sensitive question without revealing what you're asking — or who you are?
For the warfighter, even a public-data query can expose identity, intent, and operational context. WHISPER explores how to preserve that confidentiality while still retrieving useful information.
Let's build something that has to work.
If you're looking for someone who can take an open technical question and ship a working system around it, I'd like to hear about it.