I am Antonio, an MPhil student in Machine Learning and Machine Intelligence at Cambridge University. Before starting my master's, I completed a BSc in Mathematics at VU Amsterdam, where I worked on my thesis in collaboration with CRM Barcelona, studying how quenched variability affects memory storage in recurrent neuronal networks, guided by Daniele Avitabile and Alexander Roxin. I also completed a research internship at Artificial Neural Computing, focusing on the boundary dynamics of neural networks. Additionally, I co-founded altan.ai, a startup aimed at automating workflows using AI, and I had the opportunity to teach courses in Single Variable Calculus, Probability Theory, and Linear Algebra as a Teaching Assistant at VU Amsterdam.

Before shifting to AI, I earned a BA in Global Studies from Pompeu Fabra University, where I developed a strong foundation in business and economics through an interdisciplinary program. While I still enjoy diving into discussions about global politics, economics, and pressing world issues, I decided not to pursue a career in that field. After a period of self-learning and exploration, I decided to commit myself to tackling what I believe to be one of the greatest challenges of this century: understanding the workings of the brain and, more broadly, the nature of intelligence.

I am interested in exploring the computational principles of natural and artificial intelligence, aiming to "reverse engineer" the brain's algorithms, both to learn about how our brains work and to build more effective AI systems. In the long term, my goal is to leverage AI to help people gain greater agency over their circumstances and reach their full potential. I particularly want to focus my research on areas such as adaptation, abstraction, generalization, knowledge representation, computational neuroscience, and reinforcement learning.