I’m a cognitive scientist and data scientist with interdisciplinary background in neuroscience and machine learning. I’ve recently finished my PhD at the University of Oxford, where I investigated how the human brain represents multiple tasks without interference. I used deep artificial neural networks as computational models, designed and executed behavioural and neuroimaging studies with human participants and analysed large, high-dimensional datasets using state-of-the-art statistical techniques. If you’re academically inclined, you can have a look at my publications to learn more about this work.
On the side, I was active as Data Science consultant for Oxford Strategy Group Digital, the UK’s largest student-run digital consultancy, where I led and completed several data science projects with international clients in industry. A project I’m particularly proud of is AutoCausality, a Python toolbox that applies AutoML to causal inference. During my time as PhD student, I was also involved as machine learning researcher in a project with the Oxford Artifiial Intelligence Society, where I investigated how Reinforcement Learning techniques can be used to optimise purchasing decisions for cloud computing resources.
After my PhD, I spent some time at the Gatsby Computational Neuroscience Unit supported by an MRC transition to postdoc award where I was using mathematical tools from deep learning theory to build computational models of neuroscientific phenomena. Currently, I apply my technical skills at Phytoform labs, where I’m working on an AI system that supports the genetic design of more sustainable crops.
PhD in Experimental Psychology (Computational Neuroscience), 2022
University of Oxford
Master's studies in Computational Statistics and Machine Learning, 2018
BSc in Cognitive Science, 2015