Turning chemistry into a product system with commercial scale.
One of the central problems in food systems is that freshness is usually managed by approximation. Dates, assumptions, and fixed process rules stand in for actual condition. That approach is simple, but it leaves money, quality, and decision-making on the table.
The goal of this work was not just to create an interesting sensor. The goal was to build a product and data system that could translate real chemical signals into usable operational value — and do it at commercial scale.
Traditional freshness management depends heavily on proxies. Time since production, storage requirements, and expiry labelling all matter, but none of them directly tell you what is happening in the product at the moment you need to make a decision.
Food — especially protein — changes dynamically. Temperature exposure, packaging, logistics interruptions, and handling all influence spoilage behaviour. Two items with the same date code may not be in the same condition.
Freshness is not fundamentally a calendar problem. It is a signal problem.
If spoilage produces measurable chemical indicators, then freshness can be sensed, modelled, and acted on more directly than legacy systems allow. That opens the door to better decisions across shelf life, quality control, logistics, and consumer experience.
I worked on sensor concepts and development approaches tied to spoilage-related chemistry — including biogenic amine and ammonia pathways. The work involved both the physical sensing side and the system around it.
This was not just lab science and not just product design. It sat in the middle — where technical performance has to become something a business can actually use.
The hardest part of this kind of work is translation. A chemistry result is not a product. A sensor response is not a business system. To become valuable, the work had to survive multiple translations:
That required technical rigour, prototyping discipline, supplier engagement — including international inlay partners — and an understanding of where companies would actually trust and deploy a freshness signal.
The broader work contributed to billions of dollars in commercial and consumer value, supporting a shift toward more dynamic, condition-aware quality systems. It also helped establish a path for freshness sensing not as a novelty, but as an operational tool.
The important outcome was not just that the sensor functioned. It was that the concept could support real-world decision-making at scale.
This is the kind of work I'm drawn to: places where the science is real, the commercial stakes are high, and the answer is not obvious. I'm comfortable at the boundary between chemistry, engineering, and product strategy — building systems that make invisible conditions legible and useful. That is often where the biggest opportunities are hiding.