I am a Post-Doctoral Researcher at the University of Cagliari (Italy), working at the Physics Department, in the “Molecular Modelling” group.
Graduated in Physics, since my bachelor’s degree, I realized computational physics and data analysis were among the subjects I liked the most. For this reason, when looking for my bachelor’s degree thesis, I tried to combine those subjects with some other personal interests. In doubt between Computational Geophysics or Biophysics, I ended up choosing the latter, and working on the role of the aqueous solvent in the extrusion of substrates (e.g. antibiotics) by bacterial efflux transporter proteins.
Then I remained in the same field also for my master’s degree thesis, this time working on a computational protocol to improve the predictive power of molecular docking, a technique used to reproduce the three-dimensional structures of protein-ligand complexes starting from the unbound partners (check "EDES tutorial" in the Project page). I went on working on the same project also during my Ph.D., which I ended in early 2020.
Later that year, I started becoming intrigued by “Machine Learning" and its manifold applications. For this reason, I enrolled in a postgraduate specialization in "Machine Learning and Big Data for Biomedical applications", offered by the University of Padua, from which I graduated in September 2022.
At the moment, my job as Post-Doctoral Researcher is focused on: (i) applying EDES protocol in a virtual screening scenario (ii) building machine learning pipelines to predict protein properties (e.g. druggability, stability); (iii) studying the functioning and inhibition of bacterial multidrug efflux using computational tools; (iv) investigating the allosteric behavior of serotonin receptors when bound to agonist/antagonist compounds via computer simulations.
Other than that, my passions include programming, ancient philosophy, fitness and outdoor activities.