Reminder - Spotlight Seminars: Prof. Fabrizio Silvestri TODAY April, 30 2026 – 5:00 PM
Gabriella Cortellessa
Dear members,
We would like to remind you of this afternoon’s seminar.
We look forward to your participation and hope to see many of you there.
============================================================The Italian Association for Artificial Intelligence is pleased to announce the next seminar of its Spotlight Seminars on AI initiative:
Date and Time: April, 30 2026 – 5:00 PM (CEST)
Online attendance: The seminars will be held virtually on the YouTube channel of the Association (https://www.youtube.com/c/AIxIAit),
Title: Learning with Structured Consistency: Sheaf Neural Networks from Theory to Applications
Speaker: Prof. Fabrizio Silvestri - Sapienza, University of Rome
Abstract: Modern machine learning on graphs is largely built on the assumption that neighboring nodes should be similar, an inductive bias that breaks down in the presence of heterogeneity, multi-modality, and relational ambiguity. Sheaf Neural Networks offer a principled alternative by replacing this notion of similarity with structured consistency: information is no longer directly compared across nodes, but aligned through learnable transformations defined on edges and, more generally, on higher-order relations.
In this talk, I introduce the sheaf-theoretic perspective as a natural and flexible framework for learning over complex relational data, spanning both graphs and hypergraphs. I will motivate the approach through concrete failure modes of standard Graph Neural Networks, and show how sheaves provide a unified solution to modeling directionality, heterophily, and context-dependent interactions, while naturally extending to higher-order structures beyond pairwise connections. I will then present a sequence of theoretical results that characterize the expressivity, stability, and spectral properties of Sheaf Neural Networks, highlighting their role as a strict generalization of classical architectures.
Finally, I will illustrate how these ideas translate into practice through applications in recommender systems, where modeling structured inconsistency leads to significant empirical improvements. I conclude by discussing open challenges and future directions, including scalable learning of sheaf structures on hypergraphs and connections to broader geometric deep learning paradigms.
Bio: Fabrizio Silvestri is a Full Professor at Sapienza, University of Rome in Italy. Formerly a Research Scientist at Facebook AI in London. His interests are in AI applied to integrity-related problems and Natural Language Processing. In the past, he has worked on web search research, and in particular, his specialization is building systems to interpret better queries from search users. Before Facebook, Fabrizio was a principal scientist at Yahoo, where he had worked on sponsored search and native ads within the Gemini project. Fabrizio holds a Ph.D. in Computer Science from the University of Pisa, Italy, where he studied problems related to Web Information Retrieval with a particular focus on Efficiency-related problems like Caching, Collection Partitioning, and Distributed IR in general.
AIXIA spotlight seminars: The seminar series aims to illustrate, explore and discuss current scientific challenges, trends, and possibilities in all branches of our articulated research field. The seminars will be held virtually on the YouTube channel of the Association (https://www.youtube.com/c/AIxIAit), every month (and made permanently available on that channel), by leading Italian researchers as well as by top international scientists.
The seminars are mainly aimed at a broad audience interested in AI research, and they are also included in the Italian PhD programme in Artificial Intelligence; indeed, AIxIA warmly encourages the attendance of young scientists and PhD students.
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The Spotlight Seminars on AI Committee,
Giuseppe De Giacomo
Antonio Lieto
Luciano Serafini