Building AI systems for uncertain environments — from UAV autonomy research to enterprise agentic workflows.
Computer Science & Engineering graduate from the University of Toledo. My work spans autonomous drone systems, enterprise AI, sports analytics, and data engineering. Not by design, but by instinct: I go where the hardest problems are.
The skill that transfers between fields isn't domain knowledge — it's knowing how to ask the right question when you don't have home-field advantage.
A system someone can't override isn't autonomous — it's unpredictable. The recovery mechanism is part of the design, not an afterthought.
Real edge cases, latency requirements, stakeholders who need to understand the output. That pressure makes the work honest.
Where the work actually happened.
Each project a different operating condition. Click any card for the full case study.
Thinking in public — dispatches from the edge of AI, robotics, and real-world systems.
Published work and ongoing investigations.
Training distributions that diverge from deployment conditions. The initiating mechanism in 18 of 37 documented failures.
Monitoring blind spots that allow small deviations to compound undetected until failure becomes irreversible.
Systems that perform on benchmarks but fail at the boundary of their training manifold under novel real-world inputs.
Emergent failure modes from agent interactions producing unsafe equilibria that are absent in single-agent testing.
Technical stack built across research, industry, and deployment.
Qubit state manipulation, superposition principles, and measurement postulates. Foundational for quantum circuit design and quantum-enhanced autonomous systems research.
Press coverage and public recognition.
What I'm actively learning, building, and chasing outside of work.
Whether it's a full-time opportunity, research collaboration, or just a conversation about autonomous systems — I'm listening.
