Writing
Monthly posts on AI, statistics, development data, and the occasional adventure. Professional insight with practical implications.
Lessons from designing a machine learning training programme for government statisticians in Cambodia — what works, what doesn't, and what I'd do differently.
How statistical sampling and analysis underpin accountability in development finance — and why getting the methodology right matters more than you think.
The hidden infrastructure behind food security policy — and what happens when the data isn't there.
How experience in commercial market research made me a better development statistician — and vice versa.
Separating what actually works from what sounds good in a grant proposal. A field perspective.
Planning, pacing, adapting, and the art of not quitting when everything hurts. Lessons that transfer.
Published work