Infrastructure
Our infrastructure is built for reproducible research: disciplined data handling, transparent compute, and results that can be re-run.
System manual
How the work holds together, read as a directory. Each group expands to the discipline behind it — kept at the level of what we do, not the proprietary detail of how.
Dataversioned
We treat data as the foundation that every result rests on. Sources are acquired deliberately, validated on the way in, and versioned so that the exact inputs behind a finding can be recovered later. Cleaning and transformation steps are recorded rather than improvised, keeping the path from raw source to research-ready dataset auditable.
Compute & Researchrepeatable
Research runs in environments built for repeatability. Experiments are configured so the same analysis produces the same result, and exploration is kept separate from work that is ready to stand behind. The aim is that reproducibility is a property of the system, not an afterthought.
Reproducibilityauditable
A result is only as credible as the trail behind it. We keep the artifacts that let a finding be re-run — the inputs, the steps, and the code that produced it — so that what we publish can be checked rather than taken on trust. Where work reaches that bar, the accompanying repositories and preprints make the reasoning legible without exposing the full method.
Engineering Culturereviewed
How we build matters as much as what we build. Research is version-controlled and reviewed, pipelines are tested before they are relied on, and a clear line separates exploratory work from the production research that supports a published claim. The discipline is deliberate: it is what lets the work be extended, re-run, and trusted as the body of research grows.