As a Ph.D. student at Sapienza University of Rome, I am part of the GLADIA research group led by Emanuele Rodolà. With a background in Computer Science and Engineering from the University of Verona (2021), I specialize in Geometric Deep Learning, Geometry Processing, and 3D spectral shape analysis.

My research interest lies in exploring the intersection of geometry processing and graph learning, with a particular emphasis on utilizing spectral techniques in graph analysis. My current research directions encompass:

• Apply vector quantile regression to data that lies on manifolds.
• Analyzing biomolecular interactions from a geometric perspective.
• Investigating the use of spectral structures to represent graphs.

I am proud to have received recognition for my Master’s thesis with the Best Italian Master Thesis in Computer Graphics (Matteo Dellepiane award) at the Italian Chapter of EuroGraphics (STAG). In March, I joined the research group of Alex Bronstein at Technion (Israel) to start a collaboration on vector quantile regression applied to manifolds and geometric analysis of aromatic molecules.