Hello! I am a Computer Science student at Lancaster University, and I am truly passionate about the entire journey of software development, from the first spark of an idea to a fully deployed application. For me, the most exciting part of this field is the challenge of solving complex problems and turning those solutions into something tangible and useful.
My professional experience at DigbySwift was a fantastic opportunity to dive into the world of mobile development. Working with Dart and Flutter, I got hands-on experience building a cross-platform app, which taught me the importance of writing clean, testable code and managing projects effectively using Git.
When I'm not studying, I love to use my skills to explore my personal interests. As a big UFC fan, I was curious if I could predict fight outcomes, which led me to build a machine learning model in Python. By cleaning and analyzing a dataset of over 6,000 fights, I was able to train a model that achieved a 66% accuracy rate. I've also enjoyed bringing classic algorithms to life by creating a pathfinding visualizer in Java that can find the shortest route through a tram network using Dijkstra's algorithm.
I am always looking for new challenges and ways to grow as a developer. I am excited by the prospect of bringing my mix of academic knowledge and practical, hands-on experience to a new and challenging software engineering role.
A machine learning application that uses a logistic regression model to predict UFC fight outcomes and serves the predictions through a containerized FastAPI application.
Advanced Java application implementing Dijkstra's algorithm and custom pathfinding for optimal tram route calculation with GUI visualization and delay simulation.
2D racing game built with Pygame featuring multiple tracks, car selection, competitive mode with tire degradation, and local leaderboards.
I'm always interested in new opportunities and exciting projects. Whether you're a recruiter or looking to collaborate, let's connect!