Biography

I graduated from the Computer Science Department of the University of Milan in 1990 (Laurea Degree) specializing in logic-based Artificial Intelligence. From 1990 to 1992 I was a Research Assistant in the same department carrying out research in mathematical logic and automated theorem proving. From 1992 to 1996, I took part in a cooperative project for Third World Countries development, aimed at creating a Computer Science programme at the Catholic University of Asunción, Paraguay. At Asunción, I taught several computer science courses and started two research groups, on automated theorem proving and machine learning.

In 1996 I joined the postgraduate programme in Computer Science at the University of Toronto, obtaining my PhD in 2002. From 1999 to 2002, I carried out my research at the Gatsby Computational Neuroscience Unit. During my PhD I specialised in machine learning under the supervision of Prof. Geoffrey E. Hinton. I was predominantly involved in basic research, and in my thesis I introduced Linear Relational Embedding, a new method for solving the problem of learning symbolic relationships from examples.

After completing my PhD, I moved towards Computational Biology. From 2002 to 2006 I was a postdoctoral associate, first at the Genome Centre of Queen Mary University of London (in Mansoor Saqi Lab) and subsequently at the Department of Molecular Biophysics and Biochemistry of Yale University (in Mark Gerstein Lab). During this period I developed novel computational approaches for clustering protein sequences, protein remote homology detection, noise reduction in protein-protein interactions, and prediction of gene essentiality from genomic features.

Since February 2006 I have been working in the Computer Science Department at Royal Holloway, University of London. I was promoted to Reader in 2008 and to Professor in 2013. In February 2020 I moved to Rio de Janeiro where I took a Professor position at the School of Applied Mathematics of FGV.
My research lies in developing novel machine learning techniques for solving problems in computational biology, medicine and pharmacology.