Bellman–Ford, explained clearly.
A practical guide to shortest paths, negative edges, negative cycles, and a Python implementation.
Writing on computing and education.
Why I write
Empathy, purpose,
and useful impact.
My background is in data science and educational analytics. I stay focused on what helps people learn, teach, and decide well — not on technology for its own sake. This site aims for writing that respects the work of others: clear enough to use, honest about evidence, and oriented to human objectives before tools.
Articles and study
Personal site writingShort articles on computing, education, and evidence — for people who teach, learn, and decide. Browse the full article list, or subscribe via RSS . This is not a publication record or portfolio of formal work.
LLM fluency is not reasoning.
What large language models are good at, where fluent answers mislead us, and how to evaluate claims about intelligence and understanding.
Computer science has two parents.
Mathematics explains the structure and limits of computation. Engineering makes those ideas work in imperfect, physical systems. Students need both.
Teaching computing beyond syntax.
What pupils need besides working code: structure, explanation, debugging habits, and the confidence to reason about programs.
PGCE Secondary Computer Science with ICT.
Current teacher training at London Metropolitan University.
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For education, computing, or data-related conversations, connect with me on LinkedIn.