Luca Becchetti

Luca Becchetti is an Associate Professor in the Department of Computer, Automatic, and Management Engineering at Sapienza University of Rome, where he has been a core faculty member since 2012. He holds a PhD and M.Sc. in Computer Engineering from the same institution and has been actively contributing to research in algorithms and network science.

• PhD in Computer Engineering, Sapienza University of Rome, 1998
• M.Sc. in Computer Engineering, Sapienza University of Rome, 1995

His research focuses on the design and analysis of algorithms for NP-hard and online optimization problems, with a strong emphasis on network design and resource allocation. More recently, his work has evolved to include large-scale information network analysis, such as the Web and Internet. Current research directions involve distributed graph clustering using spectral graph theory, modeling of complex systems, and pioneering applications in Network Medicine through advanced graph mining and spectral techniques. He is a member of research groups in Computer Networks and Pervasive Systems, Algorithms and Data Science, and the Theory of Deep Learning.

His recent publications span areas of opinion dynamics, network medicine, and distributed algorithms, demonstrating a trend toward interdisciplinary research combining theoretical computer science with biological and social network applications. Key themes include synchronization in minority dynamics, robustness in opinion models, and multi-omics integration for disease gene prediction.

He has been involved in significant research projects including the EU FET-OPEN COSIN, EU IST APPOL II, and the National FIRB WEBMINDS. While no formal list of advisees is provided, he supervises students in algorithms and data science. He teaches courses such as Big Data Computing and Web Information Retrieval.

Luca Becchetti is affiliated with the Algorithm Engineering group and the Department of Computer, Automatic, and Management Engineering (DIAG), where he leads research in distributed algorithms and network analysis.