About

Reliability is the through-line.

I lead AI and digital-transformation strategy, helping organizations turn AI into durable business value while managing the risks that come with it.

For more than a decade, I've been solving complex business and engineering problems with statistics, predictive modeling, machine learning, and data. Across nuclear energy, advanced materials, healthcare, and enterprise consulting, I've used analytics to improve decisions, optimize operations, guide strategic investments, and build products people depend on. That experience shapes how I think about AI today.

My career began in environments where reliability wasn't a goal — it was a requirement. From DOE-Q nuclear modernization programs and FDA-regulated manufacturing to Shingo Prize-winning operations, I learned that technology only creates value when it is disciplined, measurable, and dependable. As AI has become a defining business capability, I've applied that same engineering mindset to helping organizations deploy AI that is trustworthy, governable, and built to last.

"Don't play what's there. Play what's not there."
— Miles Davis

Innovation, to me, is like jazz. The breakthroughs rarely live in what's already on the page — they're in the space around it, the move no one expected. I lead innovation by listening for what's missing and building toward it.

Today I help organizations define AI strategy, modernize operating models, and translate emerging technologies into measurable business outcomes. My work spans enterprise AI strategy, digital transformation, machine learning, intelligent automation, AI governance, technology due diligence, and executive decision support. I lead cross-functional teams, advise executives on technology-investment decisions, and bridge the gap between business strategy and technical execution.

Along the way, I've led a $100M+ DOE nuclear modernization program, guided $50M+ in innovation investment decisions, built AI-driven robotics and digital-twin solutions, and developed enterprise AI platforms that help executives make better decisions.

I'm also an inventor, author, and educator. I authored The Operator's Guide to AI Agents, hold a pending U.S. patent focused on AI reliability methods, and teach Artificial Intelligence as an adjunct professor at East Tennessee State University.

I believe AI will become one of the defining business capabilities of the next decade — but only if organizations build it with the same rigor, accountability, and focus on measurable outcomes that they expect from every other critical business function.

If you're building AI that has to work in the real world — not just in a demo — I'd enjoy connecting.

At a glance

Credentials & focus

Education
MBA — Duke University, The Fuqua School of Business (2022)
AI / ML Training
Postgraduate Program in AI & ML — UT Austin, McCombs (2025)
Engineering
M.Eng, Industrial Engineering — NC State (2017)
Undergraduate
B.S., Chemical & Biomolecular Engineering — Tennessee Tech (2013)
Certifications
PMP · Lean Six Sigma Black Belt (CSSBB) · M&A Professional (M&AP)
Recognition
40 Under Forty, Tri-Cities Business Journal (2021) · Kellogg Case Competition Finalist
Teaching
Adjunct Professor of AI — East Tennessee State University
Location
East Tennessee · Open to remote

Capabilities

What I bring to the table

Three things I pin above the rest — AI strategy, data & statistical modeling, and AI governance & reliability — built on a deep technical toolkit.

AI Strategy Data & Statistical Modeling AI Governance & Reliability Machine Learning Predictive Analytics Design of Experiments (DOE) Statistical Process Control (SPC) Python R JMP Minitab Power BI Digital Transformation Enterprise AI Adoption LLMs & Generative AI Agentic Systems Intelligent Automation Program & Portfolio Management (PMP) Executive & C-Suite Advisory Change Management