Computer Scientist / Neuroscientist
I am a Computer Scientist with a particular interest in the study of what I consider to be the most beautifully engineered computing architecture: the human brain.
My history starts in Patagonia, where I grew up. I slowly started migrating north. I first moved to Buenos Aires where I enrolled in a bachelor and masters in Computer Sciences at the University of Buenos Aires. During my first years, I was fascinated by how low-level mathematical and logical operations could produce highly-complex graphical and intelligent systems. Later on, I enrolled in a PhD to continue working on signal processing in brain signals. I kept moving north, crossed the Atlantic and converted my PhD into a joint PhD (cotutelle) between the University of Buenos Aires (computer sciences) and Sorbonne University (cognitive neurosciences). My PhD focused on the study of consciousness, where I employed machine-learning and data-driven models to diagnose patients with disorders of consciousness and study the relation between cognition and global states of consciousness.
After my PhD, I migrated north again and became a post-doctoral fellow at the University of Liège in Belgium, where I continued discovering and unravelling the mysteries of the human mind, keeping in mind the clinical applications. However, after experiencing the needs of clinical researchers, patients and caregivers, I realised that the promise of artificial intelligence as a knowledge-enhancing methodology in clinical domains is still far from being real: we need explainable, accountable and transparent AI.
To this end, I decided to go back to my origins, back to Computer Science. I am currently the leader of the Research and Infrastructural Software Engineering for ML (RISE-ML) team in the Applied Machine Learning group, at the Institute of Neuroscience and Medicine - Brain and Behaviour (INM-7), where I do research developing algorithms and methods for trustable AI.
Overall, my research is centred on developing algorithms and processing high volumes of data in order to use state-of-the-art computing technology to answer scientific questions about human consciousness and cognition.