I build AI-accelerated operations research solutions for warehousing, logistics, and the cold chain.

Live 3PL deployments and seven-figure outcomes. Currently at Americold; building toward the intersection of applied OR and AI in supply chain operations.

01

The reframe before the optimizer.

Most operations problems are stated wrong on first reading. The leverage usually lives in a framing nobody has questioned — a column in a report meaning something different from its name, a daily average blending three populations, a "demand" curve that's actually a processing rate.

02

Operations research at LLM-velocity.

Formulation, validation, and deployment cycles compressed from quarters to weeks. The mathematical rigor stays intact; the syntax gets generated under direction. This is what AI-accelerated means in practice — not a vendor platform claim, a workflow.

03

Rigor that holds up in three rooms.

The warehouse floor, where standard work has to survive contact with a real operator. The GM's office, where the analysis has to translate into a decision. Peer review, where the methodology has to defend itself against people whose job is finding the flaw. The work has to land in all three.