Hello, I am

Joseph Da Costa

Final-year Computer Science student at Queen Mary University of London, on track for First-Class Honours, with a year of industry experience as a Software Engineer at Amplifi Capital. I enjoy solving real-world problems with clean, scalable software. From full-stack development and Java microservices to AI projects in deep learning and game development in Unity. I'm actively seeking opportunities in the tech industry where I can contribute to impactful products, grow my engineering skills, and collaborate with others to build meaningful solutions.

Resume

Qualifications

Education

Work

GCSEs

11 GCSEs ranging from grade 9-5
2016 - 2019

A-Levels

Economics (A*), Mathematics (A*), Physics (A)
2019 - 2021

Computer Science

Queen Mary University of London
2021 - Now

CS50

Web Programming Course by Harvard University
SEPTEMBER - DECEMBER 2022

Scrimba

React Router 6 Course by Scrimba
MARCH - MAY 2023

Projects

TESLA CLONE

Responsive website that replicates the design and functionality of the official Tesla website, it includes a landing page, product information and car gallery

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 at Rocket Padel Ilford using Puppeteer It scans availability for the next 7 days and logs open time slots in a structured format.

FINAL YEAR PROJECT

This project developed an AI system that classifies human emotions by analyzing eye movement patterns (fixations, saccades) and pupil dilation using a bidirectional LSTM model, achieving 75% accuracy.

CIFAR-10_CLASSIFICATION

A PyTorch implementation of a custom neural network architecture for CIFAR-10 image classification, featuring attention mechanisms and data augmentation.

Contact