I recently completed my Master's in Informatics and Computing Engineering at FEUP, graduating
with a final grade of 18/20. My thesis, “Generalized Prototypical Parts Siamese Networks for
Explainable Identity Recognition”, was awarded 19/20 and focused on developing two novel AI
architectures to make facial recognition more transparent and trustworthy.
My background gave me solid expertise in machine learning, deep learning, and computer vision
(primarily with Python), but my professional interests extend well beyond AI. I'm passionate
about software development as a whole, from building modern web applications and backend systems
to designing user-friendly mobile apps and experimenting with game development.
I enjoy building practical, user-focused solutions and thrive on solving complex problems that
make a meaningful difference. I believe technology should empower people and improve daily life
in responsible ways, and I'm excited to bring that mindset to the projects and teams I work
with.
Conducted research under a scientific initiation grant on explainable facial recognition solutions and published a scientific article to ICCV.
Developed DevOps solutions using Microsoft Azure Cloud, integrated with CI/CD pipelines and Infrastructure-as-Code automations with Terraform.
Final grade: 18/20
Final grade: 18/20
Project written in C for Minix that implements custom drivers for the following devices: timer, keyboard, mouse, video card, real-time clock, and serial port. This project accomplished perfect harmony between all devices, converging into a smooth animated multiplayer chess game.
A fully functional website built with base HTML, CSS, PHP and JavaScript, featuring a responsive design. It supports AJAX requests for dynamic content loading and includes a custom-built admin panel for managing the website's content.
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