I learn fast. I build faster.
MSc Computer Science student at the University of Liverpool. I pick up new tools quickly, work well in teams, and turn ideas into real working products. Whether it's a web app, a data project, or something I've never done before — I figure it out and ship it.
I'm the kind of person who gets thrown into something new and figures it out. During my MSc I've gone from writing my first lines of Python to building a live full-stack web application, a network analysis tool, an earthquake visualiser, and a statistical analysis project — all from scratch, all documented, all working.
I don't come with years of industry experience. What I do come with is a genuine curiosity, a habit of reading the documentation properly, and the stubbornness to keep going when something doesn't work. I've debugged API authentication issues at midnight and still shipped the feature by morning.
I communicate clearly, I work well in a team, and I'm comfortable taking ownership of a task and seeing it through. I'm looking for a role where I can keep learning quickly and contribute from day one.
Four projects across web development, data analysis, and visualisation — each one solving a real problem with real data.
A full-stack web application that tracks live UK trains on an interactive map. The core challenge: train APIs don't provide GPS coordinates — so I built an algorithm that estimates train position between stations using time-based interpolation. Users can search any UK station, view live departures, monitor journey progress, and set delay alerts.
Used graph theory and OpenStreetMap data to analyse street connectivity across Liverpool. Identified high and low walkability areas using node degree as a connectivity measure, with results presented through static and interactive maps.
Pulls live earthquake data from the USGS API and visualises magnitude, location, and depth through both static and interactive maps. Marker size and colour encode severity at a glance — making complex global data immediately readable.
Comparative analysis of three datasets using Pearson correlation, linear regression, and R-squared — making the case that visualisation is essential because summary statistics alone can be deeply misleading.
A mix of technical tools and soft skills. I'm not a specialist in one narrow area — I'm someone who can pick up what a project needs and make it work.
I'm open to graduate roles, internships, and anything interesting. If you think there might be a fit — or you just want to see more of my work — reach out.