Caroline Morton

Specialist Rust consultant for performance-critical, scientific, and data-intensive systems — with a unique background in medicine and epidemiology.

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Caroline Morton
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Consulting

I take on high-end Rust consulting for performance-critical and data-intensive systems, plus the data engineering around them. My clients span education, healthcare, gaming, and research institutions.

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Rust

I use Rust where performance, accuracy, and reliability matter most — high-stakes systems that need to be both fast and correct. Its strong type system catches whole classes of bugs before they ever ship.

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Open Science

I advocate code sharing and open science in health research, teaching researchers software best practices for transparent, reproducible research. I also build open source tools to help researchers.

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Want to know more?

I specialise in Rust for performance-critical, scientific, and data-intensive systems, including synthetic data generation. Drop me a message if you’re working on a challenging performance or data problem, or want to explore how we might work together.
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Women in Rust

Women in Rust

I am the co-lead of a community group that aims to support Women in the Rust programming language.

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My Blog

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What is a directed acyclic graph (DAG)?

How directed acyclic graphs (DAGs) help epidemiologists separate causal from non-causal paths, and decide which variables to adjust for in health data research.

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Why I teach a workshop on codelists

Codelists decide which patients end up in a study, but building one is rarely taught as a method. This post explains why I run a three hour codelist workshop for universities and what it covers.

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What is the difference between selection bias and sampling bias?

A reference guide to the difference between selection bias and sampling bias in health data research, with worked examples of how each one distorts your results.

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