As part of my final year university project, I created an application for gym-goers to analyse videos of barbell exercises. Using machine learning and computer vision techniques, the application features the ability to classify images/videos of exercises being performed into squat, bench press, or deadlift. The app also traces out the bar path, plots motion graphs, and validates form.

I worked as the lead back-end developer on a university software development group project. We built a platform to match mentors and mentees to each other based on a compatibility heuristic, allowing them to schedule meetings, send messages and more. The full stack, highly scalable web application was made using Node.js and Django and deployed with Docker.

I wrote a parser and interpreter for a custom programming language using JavaCC as part of a university coursework. The language has a specific syntax, such as a exact formatting of brackets and curly brackets, which must be followed for a program to be parsed and interpreted successfully. This coursework received a perfect mark.

I produced a python program to assign comedians to slots
of a comedy show schedule in a way that minimises a cost heuristic, while satisfying a set of constraints. This university coursework tested my understanding of AI techniques such as stochastic greedy hill descent and backtracking which I demonstrated in my solution.