Solving all disease at Isomorphic Labs. Previously, I completed an MPhil in Advanced Computer Science with Distinction at the University of Cambridge, researching Geometric Deep Learning, Neural Algorithmic Reasoning, Mechanistic Interpretability, and the optimization of Machine Learning Systems. Prior to that, I graduated with a BSc in Computer Science and Engineering from the Technical University of Lisbon, ranking 1st out of 360+ students. During my undergraduate studies, I also researched classical satisfiability algorithms for gene regulatory networks.
MPhil in Advanced Computer Science, 2024 - 2025
University of Cambridge
BSc in Computer Science and Engineering, 2021 - 2024
Instituto Superior Técnico - University of Lisbon
Bayesian approach to predict the severity of an avalanche in a given region, and identification of the optimal location for dam placement and avalanche mitigation. Bayesian Optimization, Multi-fidelity, Sensitivity Analysis, Gaussian Processes, etc.
A machine learning pipeline for prediction of asset value using a customly designed LSTM model. Developed efficient pipelines for API data extraction, web-scraping, cleaning, and preprocessing data from hundreds of sources. All-time-high accuracy of about 64% (insane I know, learned patterns didn’t hold for long though, if only I had invested all my money during those glorious weeks…). PyTorch, Tensorflow, Keras, Numpy, Pandas.
Web application allowing for the creation and conversation with an AI-generated psychologist. LLMs, Speech Synthesis and Voice recognition to create a realistic therapist character and enable a fluid conversation with the user. Node.js, React, AWS.
Coded a compiler for a made-up language supporting recursion, conditionals, loops, etc. From scratch (no libraries), in C++.
Coded a filesystem from scratch, in C, supporting concurrent access, multithreaded operations, and implemented a message broker on top of it.