Hello, I am
Joseph Da Costa
First-Class Honours Graduate in Computer Science from Queen Mary University of London, with a year of professional experience as a Software Engineer at Amplifi Capital, complemented by infrastructure and DevOps exposure at Hiro Capital. I am passionate about building clean, scalable software to solve complex, real-world problems. My hands-on experience spans full-stack development, Java microservices, cloud infrastructure and innovative AI projects in deep learning. I am now seeking a challenging role where I can apply my proven technical and academic skills to develop impactful products and contribute to a collaborative engineering team.
Resume
Qualifications
Education
Work
GCSEs
11 GCSEs ranging from grade 9-5A-Levels
Economics (A*), Mathematics (A*), Physics (A)Computer Science
Queen Mary University of LondonFirst-Class Honours (1st)
CS50
Web Programming Course by Harvard UniversityScrimba
React Router 6 Course by ScrimbaProjects
NETFLIX CLONE
Built a Netflix clone using ReactJS, Firebase for auth and database, Styled Components for UI, and Fuse.js for live search. Includes Sign In/Up, Home, and Browse pages.
MERN DISCORD CLONE
A real-time Discord clone built with MERN, Firebase Auth, Pusher for live messaging, and Postman for API testing, featuring channels, DMs, and secure user authentication.
WEATHER APP
Created a weather app for university students using APIs from weather and TFL. Allows users to check weather and transport info for their location.
WEB SCRAPER
Created a script which automates checking for available booking slots on a Rocket Padel website using Puppeteer. It scans availability for the next 7 days and logs open time slots in a structured format.
FINAL YEAR PROJECT
This project researched and developed an AI system that classifies human emotions by analyzing eye movement patterns and pupil dilation using a bidirectional LSTM model, achieving 75% accuracy.
CLASSIFICATION MODEL
A PyTorch implementation of a custom neural network architecture for CIFAR-10 image classification, featuring attention mechanisms and data augmentation.