Wake Up Babe, New Quarto Product Just Dropped
A first look at Quarto’s new great-docs package, why I care, and why I think it might finally give…
Apr 15, 2026
R + Python | Reproducibility | Open and FAIR science
Research Software Engineering for Reproducible Science
Notebook-driven, reproducible workflows for scientific teams.
I build notebook-native, reproducible workflows for scientific teams.
My work sits at the intersection of research software engineering, data science, and scientist enablement. I have experience across neuroimaging, psychology, human-computer interaction, and climate-focused research, and I care most about turning exploratory analysis into maintainable, testable, reusable software.
I am especially interested in notebook-driven development, computational reproducibility, and helping early-career researchers become effective programmers in R and Python.
What I Bring
Reproducible workflows
I design pipelines, environments, and reporting systems that are easier to rerun, review, and hand off across teams.
Notebook-driven development
I like starting where scientists already think and work, then shaping notebooks into packages, services, and durable project structure.
Open and FAIR practice
I care about code, data, and documentation that are transparent, discoverable, and useful beyond a single deadline or paper.
Scientist enablement
I enjoy mentoring and building training material that helps young researchers write better R and Python with more confidence.
The Kinds of Problems I Like
- Translating research questions into robust analytical software
- Cleaning up the gap between exploratory work and production-ready workflows
- Improving documentation, testing, CI/CD, and environment management
- Making it easier for labs and data teams to sustain their own tools
Where I Have Context
- Neuroimaging and behavioural science
- Psychology and human-computer interaction
- Data science in both academic and industry settings
- Climate, health, and other cross-disciplinary research workflows
Recent Writing
I write about research software engineering, notebook-driven development, R/Python tooling, and the everyday work of making scientific computing more reproducible.
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Building Better Systems for Science
I strive to be a leading research software engineering specialist in notebook-driven development and reproducibility. I am most useful to teams that need someone who can bridge scientific context, engineering discipline, and practical training.