Hi! 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.