Rust

I write Rust professionally through my consultancy Parakeet Consulting. Most of my work is backend services and data-intensive systems: API design, gRPC and HTTP servers, state machines, data pipelines, and scientific computing. My clients span gaming, healthcare, medtech, and fitness.

I came to Rust from Python and epidemiology. We rewrote the entire backend of my medical simulation platform Clinical Metrics from Python to Rust, and the performance improvements were significant. I am now completing a PhD in medical statistics where I am building synthetic data generation tools in Rust. My RustConf 2026 talk, “Simulating a Million Patients: Realistic Health Data Generation in Rust”, covers this work.

I co-lead Women in Rust with Lizzie Holmes, a community working to increase the representation of women in the Rust ecosystem (currently around 3% of Rust developers). We run regular meetups and events. Join the meetup group for event notifications or the LinkedIn group to connect with members.

I speak regularly about Rust at conferences, most recently at Rustikon in Warsaw and RustConf in Montreal. See my speaking page for a full list.

See my uses page for the tools and libraries I use in my Rust projects.

Logs and tracing in Rust: From Terminal to Grafana

How to ship structured logs from a Rust application to Grafana Loki and query them, with a complete local setup using Docker Compose.

Logs and tracing in Rust: Structured Fields and Spans

How to use structured fields and spans in the Rust tracing crate to add context to your logs and understand the flow of execution in your code.

Logs and tracing in Rust: Fundamentals

An introduction to logging and tracing in Rust, covering some of the philosophy behind logging and how to set up a basic tracing subscriber in your Rust projects.

Gaming Studio (NDA)

Backend services development at a major international gaming studio. Over 2 year contract working on a variety of projects including API development, data pipelines, and internal tools.

Why Rust for Data-Intensive Applications

Explores why Rust matters for research data pipelines - not for performance, but for correctness. Learn how Rust’s type system prevents data failures.

Your Errors Are Data Too

How Rust’s error handling patterns let you treat errors as structured observations about your data - capturing context, categorising failures, and producing data quality reports as first-class pipeline outputs.

Why Use Newtypes? Encoding Domain Knowledge in the Type System

How Rust’s newtype pattern lets you encode domain knowledge - valid ranges, clinical thresholds, meaningful operations - directly into the type system, so the compiler enforces what you already know to be true about your data.

Serde Rust: Data Serialisation for Data Scientists

Practical Rust patterns for building validated data pipelines with Serde. Custom deserialisers, domain-constrained types, streaming CSV processing, and structured error handling for messy real-world data.

Accidental Functional Programming in Rust (From an Epidemiologist's Perspective)

Rust quietly pushes you into functional patterns. An epidemiologist explains Result, match, enums, iterators, and when readability beats idioms.

Error Handling in Rust: anyhow and thiserror

Practical Rust error handling beyond the basics: add context with anyhow and define typed errors with thiserror.

Error Handling in Rust: Fundamentals

A clear, practical guide to Rust error handling: panic, Result, ?, unwrap, and expect - written for Rust developers who want clarity without jargon.

Women in Rust 2025

Celebrating another wonderful year of women making strides in the Rust programming community.

Clinical Metrics

A medical simulation tool for training doctors in the UK

DIVINA

A medical simulation tool for training medical students in Germany

Finding Similarity with Vector Search: A Beginner's Guide

This blog comes out of an interactive workshop I gave using SurrealDB. It’s a beginner’s guide to vector search, a modern way to find matches based on multiple preferences at once.

Macrodash

A dashboard tool for clients and personal trainers to track and monitor their clients’ progress with nutrition and fitness goals

A PhD in generating synthetic health data

This is an introduction to my PhD project and what I am hoping to achieve with it, which is to develop methods for generating realistic synthetic health data. This project is generously sponsored by SurrealDB, a multi-model database entirely written in Rust. I am using SurrealDB for a number of reasons, including its ability to do complex queries, vector searching and embedding functions that are useful for generating synthetic data.

Halfloop

A post-market surveillance tool for medical devices