I am a PhD student in the Ewald Lab at EMBL-EBI, working at computational biology applications and machine learning methods for environmental toxicology. I hold master’s degrees in Computer Science and Engineering and in Bioinformatics for Computational Genomics, from Politecnico di Milano and Università degli Studi di Milano.

Previously, I worked in the Saez-Rodriguez Lab at Heidelberg University and Heidelberg University Hospital, where I primarily contributed to AnnNet, a framework for representing and manipulating richly annotated biological networks, and OmniPath Metabo, a resource for integrating knowledge on metabolites, biochemical reactions, and metabolic interactions.

Across my two master’s theses, I investigated how biological prior knowledge can be incorporated into machine learning models as inductive bias. My work first focused on combinatorial gene-perturbation prediction, and the latter on differentiable optimization methods for metabolic modelling and prediction.

My research interests include systemic, metabolic-centric approaches to biology, and interpretable machine learning model design.

Outside academia, I enjoy traveling, hiking, swimming, cooking, discovering new cuisines and places.