Blog

Field notes on scientific software engineering, reproducibility, R and Python tooling, statistical computing, and selective machine learning.

Field notes from building scientific software in pharma and cosmetics R&D: R, Shiny, reproducibility, statistical computing, and some ML when it earns its place. I write when I’ve worked something out and it seems worth documenting — for my future self as much as anyone else.

Engineering Standards for Scientific Software
4 min
Engineering
Documentation
CI/CD
Standards

How I approach architecture, tests, documentation, CI/CD, handover, and technical training when building internal tools for scientific teams.

March 14, 2026

Running ShinyProxy Well: Docker, Operations, and Packaged Shiny Apps
12 min
R
Shiny
ShinyProxy
Docker
Deployment

What actually matters when deploying packaged Shiny apps behind ShinyProxy: Docker images, persistence, observability, and the boring operational details that decide whether…

March 14, 2026

Hello, R-Bloggers — What This Blog Is About
2 min
R
Meta

A short introduction for readers arriving via R-Bloggers — what I write about, who I am, and where to start.

February 24, 2026

Reproducible Environments for Everyone: DevContainers for Data Science Teams
13 min
DevContainers
Docker
R
Python
Reproducibility
VS Code

How to use devcontainers and a pre-built personal image to give every team member — including non-developers — an identical, low-setup R + Python environment.

November 28, 2025

LLM-Assisted Development: A Data Scientist’s Field Guide
12 min
AI Tools
GitHub Copilot
LLM
Development
VS Code
Ollama
Workflow

Honest notes on a three-layer AI stack — Copilot, OpenCode, and Ollama — from daily use in pharma and cosmetics R&D. Real gains, real failure modes.

October 14, 2025

The Reproducibility Quest: Modern Tools for R and Python Data Science
20 min
R
Python
Reproducibility
DevContainers
Docker
Package Management
Best Practices
VS Code
GxP
Pharma
Setup

A comprehensive guide to achieving reproducible data science workflows — environment setup, package management, containerization, and what reproducibility actually means in…

June 10, 2025

Statistical Tests Demystified: A Practical Guide for Scientists and Engineers
10 min
Statistics
Tutorial
R
Reference
Biostatistics

A clear, jargon-light walkthrough of frequentist statistics — p-values, error types, test selection, regression, and the things textbooks don’t tell you. Written for…

March 15, 2025

rv: The Modern R Package Manager for Reproducible Workflows
8 min
R
Package Management
Reproducibility
Rust
Modern Workflow

Discover rv, the new declarative R package manager written in Rust. Learn how it compares to renv, draws inspiration from Python’s uv, and pairs with rig for a modern R…

January 20, 2025

Staying Current in a Fast-Moving Field: Why I Built a Resources Catalog
7 min
Data Science
Machine Learning
GenAI
Resources
Lifelong Learning
Best Practices

In data science, machine learning, and AI, the pace of change is relentless. Here’s why I maintain a curated collection of resources — and why you might want to do the same.

December 13, 2024

Getting Started with Quarto for Data Science Reports
3 min
Quarto
Tutorial
Reproducibility

A beginner’s guide to creating beautiful, reproducible reports using Quarto in your data science workflow.

July 10, 2024
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