I am a PhD student in Computer Science at Bocconi University in Milan, where I work on AI solutions for understanding gene regulation. My PhD is funded by a scholarship from the Fondo Italiano per la Scienza (FIS) for the DECODE project, supervised by Prof. Andrea Tangherloni.

Before starting the PhD, I completed an MSc in Artificial Intelligence and a BSc in Mathematical and Computing Sciences for Artificial Intelligence, both at Bocconi. Since 2024 I have been part of Prof. Francesca Buffa’s group in the Department of Computing Sciences. In 2026 I spent several months as a visiting researcher at the Weatherall Institute of Molecular Medicine, University of Oxford, working in Prof. Jim Hughes’s lab on epigenomics and gene regulation.

Research interests

My research sits at the intersection of machine learning and computational biology. I am interested in how modern deep learning architectures can be used to understand the complex regulatory logic of the genome, and in what those models can tell us about disease.

• Gene Regulatory Network inference. I develop methods that reconstruct the interactions between transcription factors and their target genes from single-cell data. I explore a range of methodologies, from statistical approaches to deep learning models.

• Sequence-based models of gene regulation. I work with pre-trained transformer models of the genome, such as Enformer and AlphaGenome, and study how their learned representations can be used to infer cell-type-specific regulatory relationships.

• Cancer biology. Most of my work is motivated by cancer research, where identifying dysregulated gene programs can give insight into how a tumour progresses and where it might be vulnerable.

• Tooling for computational biology. I believe methods are only useful if other people can run them. I am the lead developer of pysigscore, a Python package for gene signature scoring across bulk and single-cell transcriptomics.

Get in touch

I am always happy to discuss research, collaborations, or anything at the boundary between AI and genomics. The quickest way to reach me is by email, and some of my code is on GitHub and on our group’s Bioinformatics Hub.