My PhD (supervised by Dr. Lawson and Dr. Gallagher) focuses on covariate information for dynamic network embedding. Embeddings are low-dimensional vector representations of entities, such as words or nodes, which have been impactful in powering large-language models. My work focuses on statical learning theory of embeddings and developing methods to compute more representative embeddings. My research interests expand beyond embeddings, and I’m generally interested in modelling and understanding underlying patterns in complex or high-dimensional data
Before COMPASS, I graduated from the University of Bologna, where I took part in the double degree program with the University of Glasgow (BSc Hons). In my final project, I explored latent variable models with Gaussian Processes.