Biography

I work across AI transformation and adoption, bringing together business judgment, data science, research, and hands-on platform development. My career has moved from consulting and business intelligence through machine learning to the organizational work of making AI useful.

Consulting, engineering, and business intelligence

My foundation combines a Bachelor of Engineering and an MBA in Nigeria with work in management consulting, technology consulting, training, and business intelligence. Those experiences taught me to understand operations and decisions before choosing a tool.

Data science, research, and the public interest

I earned an MS in Data Science at Rutgers University and moved further into machine learning, applied research, and public-interest technology. At Rutgers, I co-authored work on the State AI Readiness Index and presented the team's research at the 2025 AAAS Annual Meeting. I also co-authored a 2026 systematic review of explainable AI in healthcare.

The Rutgers State AI Preparedness Project is one example: I co-authored its published research with colleagues and presented the work at the 2025 AAAS Annual Meeting. I later co-authored a systematic review of explainable AI in healthcare published in Algorithms. In parallel, I conceived and led CHEDVI, a live public-facing health-equity data platform for Camden.

AI transformation and adoption

The work is both strategic and practical. CHEDVI shows the platform side of this practice; my transformation framework shows how I approach the organizational side.

Today I connect that background to the questions leaders face: which problem is worth solving, which use case creates value, how work and decisions should change, what capability people need, and what practical solution should be built.

Education, writing, and public work