About

I started my career as a nuclear engineer — trained to understand, model, and safely operate some of the most complex systems in the world. I bring that same systems thinking to banking, payments, risk, and AI: simplifying complex business and technology ecosystems into scalable models that perform under real-world and regulatory pressure.

That path led from nuclear engineering into quantitative finance and risk — building enterprise credit, capital, and stress-testing models, and then one of my bank's first AI/ML governance frameworks. From there I moved into technology, strategy, and innovation before taking the helm of enterprise payments.

Today I lead enterprise payments at a leading U.S. regional bank, supporting nearly $4T in annual transaction volume across consumer, corporate, wealth management, and treasury business lines. I work at the intersection of business performance, operations, technology, and risk — repositioning payments from a cost center into a product-led growth business and modernizing core infrastructure for real-time payments, embedded finance, and API-driven commercial banking.

In parallel, I have helped shape industry standards as former Chair of the FDX Commercial API Task Force and a Data & Trust Alliance working-group member. I teach applied AI and analytics at Duke Fuqua and UNC Kenan-Flagler, and advise founders, boards, and early-stage firms.

I also build with AI, not just about it. Over recent months I've prototyped real products with Claude Code and agentic workflows — building out personal applications that accelerate my productivity, adaptive learning apps and games for my kids, prototypes weekly for colleagues and potential clients, and this site. I run my own work on the same discipline I advise: re-allocate freed capacity to the highest-leverage work, meter the spend, and keep judgment in the loop. How I operate with AI →

My Leadership Point of View Download board biography (PDF)