Software Engineering · AI · Quantitative Systems
I build software systems and quantitative models that combine programming, mathematics and statistics.
Exploring complex problems through software engineering, simulation, data and mathematical modelling.
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Industry experiences
Insight & work experience programmes
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Major technical projects
Built from the ground up
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Research observations
Hourly weather & air quality
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A Level Grades
Academics
A snapshot of my public development activity and the technologies I work with.
Systems I built to answer a question. Each one has a full case study covering the architecture, the maths, what broke, and what I would do differently.
A probabilistic race-strategy engine that simulates thousands of possible F1 races to understand which decisions remain strong when the race does not go to plan.
A distributed job scheduling system I built to understand what happens when queues, concurrent workers, retries and failures collide.
A real-time strategy game built from scratch in C# and MonoGame, with resource management, combat systems and an AI opponent.
An independent research project analysing 14,000+ hourly observations to investigate how weather conditions relate to air quality.
Insight programmes, work experience and research placements across engineering, software, data and finance. Expand an entry to see what it involved and what I took from it.
Independent statistical work, written up the way a report should be, including the parts that did not hold up.
A statistical investigation into whether measurable weather conditions explain variation in urban air quality, using more than 14,000 hourly observations.
Do measurable weather conditions temperature, wind speed, humidity, pressure explain a meaningful part of the hour-to-hour variation in air quality readings?
More than 14,000 hourly observations combining weather measurements with air quality readings.
The raw data required substantial preparation before any analysis was possible: missing readings, duplicated timestamps and outliers caused by sensor faults all had to be identified and handled under a documented rule rather than removed quietly.
Correlation was used to identify which relationships were worth modelling, and regression to quantify them. Residuals were inspected in every case rather than assumed to be well behaved — a coefficient reported without checking the assumptions behind it does not mean very much.
Because the data is a time series, apparent correlations can arise from shared seasonal or daily cycles rather than a direct relationship, so those cycles were considered explicitly when interpreting results.
Courses and certifications I have worked through. Each one lists what I actually took from it rather than the syllabus, because the badge is not the point.
Communities, mentorship programmes and academic initiatives I have been involved with outside the classroom.
Grouped by what they are for, not scored out of ten. Hover or focus a skill to see where I actually used it.
How I got here, what I am working towards, and how I tend to approach a problem.
I'm a Year 13 student in Preston studying Maths, Computer Science and Statistics, and I spend most of my spare time building things that sit somewhere between software engineering and applied mathematics.
Most of what I know came from projects rather than lessons. I got interested in concurrency by writing a job scheduler that kept losing work when a worker died, and I got interested in probability because I wanted to know whether a Formula 1 team's pit stop call was actually the right one or just the one that happened to work.
Formula 1 is where a lot of that curiosity started - it's a sport where the interesting decisions are made under uncertainty with incomplete information, which turns out to be a good description of most engineering problems too.
I'm applying for Software Engineering and AI/ML degree apprenticeships so I can keep learning while working on systems that people actually depend on. Outside of that I play football and badminton.
I learn best by building. When I encounter something I don't understand, I try to turn it into a project, experiment or system I can test.
A LevelsSeptember 2025 - Present
GCSEs & Level 2 Engineering