Mattia Cervellini

Mattia Cervellini graduated in October 2025 with a MSc in Data Science and Management from Luiss Guido Carli with a score of 110/110 cum laude. His thesis, “A Machine Learning Approach for Physiological Role Prediction in Protein Contact Networks: a large-scale analysis on the human proteome” developed and tested data-driven methods for proteins’ role prediction across the majority of the human proteome. He previously completed a BSc in Management and Computer Science with 110/110 cum laude and studied at WU Vienna through Erasmus+. In 2025 he served as Design, Research and Development Intern at Luiss Guido Carli, contributing to experimental design, algorithm implementation, and novel techniques for embedding complex hypergraph structures. He is currently a PhD student at the Department of Information, Electronics and Telecommunications Engineering (DIET), Sapienza University of Rome, where he is expanding his research in graph and hypergraph learning. His research interests encompass machine learning, statistical analysis, graph and hypergraph representation learning, complex systems and large language models. His toolkit spans Python, R, SQL and C++.