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II. From the Inside Out: My Uncommon Journey Through Cybersecurity, Affective Computing, and Narcissistic Pattern Detection
I didn’t take a straight path to the edge of forensic truth.
I began with an associate's degree in Computer Science Technology — building machines, writing low-level code, understanding how systems break. That foundation led to a Bachelor's in Computer Science, where I became known less for grades and more for ideas. I wasn’t just solving problems — I was designing frameworks to understand the problem itself.
By the time I earned my Master’s in Information Security, I had already worked in high-level systems roles for telecom giants and government entities. I understood infrastructure, digital forensics, and ethical risk from the inside. But something was missing.
So I went deeper.
I entered a PhD fellowship in Emotion AI — a niche field at the crossroads of affective computing, psychology, and machine learning. There, I didn’t just study algorithms. I trained them to feel. I trained myself to listen for the micro-patterns in deception — the unspoken frequencies in language that betray intention, manipulation, or trauma.
That research birthed Witness Fracture — a forensic linguistic framework for exposing narcissistic abuse in high-conflict divorce — and The Recursive Claim — a new model for detecting deception in insurance fraud using recursive coherence.
These aren’t just papers. They are proof-of-work. Each emerged from a long arc of study, failure, field testing, and recursion. I didn’t just study the tools. I lived them. I forged them in high-stakes arenas where clarity isn’t optional — it’s survival.
This is what I bring to the field: not just insight, but insight applied.