Vision
Toward field science that observes continuously and turns observation into discovery, faster.
The bottleneck has moved
For most of the history of computational science, the constraint was access — to data, to computing, to models. That constraint is lifting. What remains is a harder problem: putting all of it to work so completely that a scientist spends their attention on the question, not on the machinery of reaching an answer.
The Fossett Lab works to close that gap for the field sciences — the disciplines that go to the world to collect evidence, from geomorphology to ecology to planetary surfaces — where data now arrive faster than any one researcher can keep up with by hand.
What we're building toward
The direction is field science that runs continuously rather than in one-off batches. A few commitments shape it.
- Observation that doesn’t stop
- Satellites revisit, sensors stream, and sites are flown again and again. Analysis should keep pace with the data as it arrives, rather than waiting for someone to start it.
- A record that accumulates
- Each observation adds to an evolving picture of what a place is and how it is changing — so the lab reasons over history, not one image at a time.
- AI as a collaborator
- Models help surface what is scientifically significant and suggest where to look next. Researchers decide what it means.
- Reproducibility by default
- Every result traces back to the data, code, and steps that produced it, so findings can be checked and built on.
- Discovery as the measure
- Success is understanding gained and decisions improved — not compute consumed.
What it looks like in practice
In practice, this means watching a region continuously — from orbit, from the air, and from the ground — and drawing a scientist's attention to the moments that matter: where a channel has shifted, where vegetation has changed, where something is worth a closer look. The infrastructure that makes this possible is necessary, but it isn't the point. The point is the science it accelerates.
Grounded in real research today
The lab's field, processing, analysis, and data services are how this vision stays grounded in real research now — and how new collaborations begin.