I turn open-weight models and open-source tools into AI that works in any industry: running where your data lives, grounded in your own documents, and tested before anyone relies on it.
Based in Birmingham, UK · Open to AI engineering roles
US accident impact risk · Transport Score a new accident report for major traffic impact.
A calibrated risk with its reasons, computed in the browser.
Replays of real project pipelines. Figures come from each project's own results.
Each project shows the problem, how it was built and tested, and the measured result, with links to the live system and the code.
Found that the popular “accident severity” label mostly tracked which traffic feed filed the report, then rebuilt an honest model on 3.2 million accidents from one consistent feed, explained it, and made it run entirely in the browser.
Classifies US consumer financial complaints into ten products with distilled transformers, finds the relevant CFPB examination procedures, and decides whether each case is handled automatically or sent to a person.
Answers questions about public NNPC information with local open-weight models. Every claim carries a quote that code checks word for word in its source, figures are checked again by a second model, and unsupported questions get a clear refusal.
Merged three public datasets into 10,864 images, trained YOLO11 and served it as an app that flags missing hard hats and vests. An independent real-world benchmark exposed a model that missed real vests; two fixes raised real-world vest recall from 0% to 50.5%.
My MSc dissertation. A five-stage agentic workflow turns a hospitality client's intake form into a consultant-grade menu brief. Each stage reads only what the approved stage before it hands over. Open-weight models draft, another model family reviews, code checks what they miss, and a consultant approves each step.
The evidence toolkit behind The Innovation Spine, a team proposal to reconnect Birmingham's Knowledge Quarter to the city centre. Route legibility scoring, wayfinder placement, traffic and collision evidence and a costed plan, shipped as an interactive map.
A four-hour build for the BCU AI Hackathon 2026. Answer 100 multiple-choice questions using only open models of 8 billion parameters or fewer, grounded in Wikipedia, with confidence scores and repeatable runs.
A web service that runs a quantum-kernel classifier against classical models on the same rows, features and tuning folds, for a cybersecurity and a medical dataset, and serves a calibrated network-intrusion triage model. Every comparison can be re-run from the public code.
I build AI that professionals can check before they trust it, and I take it through the whole lifecycle: data, modelling, validation, explanation, deployment and handover. I test models against real-world data, not only a test set, and I write down what each system cannot do.
Before AI, I studied communication and multimedia design and worked in IT support, explaining fixes to people who are not technical. I still write for the people who will use the system.
Based in Birmingham, UK. Email is the quickest way to reach me.