Rust for good: systems programming in Science and Public Health
summary
A Rust library provides code list validator for SNOMED/ICD10 rules and exposes bindings via PyO3 and extendr so R/Python pipelines load verified lists instead of failing mid‑run; a synthetic data engine samples patient DAGs with backwards DAG sampling to guarantee prevalences and runs in seconds where naive forward sims took minutes; practical speed wins include Polars (Python) 2h→5m and multiple Bevy/graph projects using Rust for high‑performance simulations.
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chapters (12)
- 0:00Rust in science and public health
- 3:19Reproducible and accessible science
- 7:52Epidemiology and code lists
- 14:41Rust libraries for epidemiology
- 21:27Synthetic data needs Rust performance
- 27:27Rust in scientific computing
- 30:57Rust tools for scientists
- 39:01Rust projects in science
- 44:17Open science and Rust tools
- 49:15Documenting scientific Rust tools
- 53:33Contributing to Rust science projects
- 55:19Q&A
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