Diversity&Inclusion @SoBigData.it




Promoting Women's Participation in Data Science and Related Ph.D. Programs

October 23rd, 10:00 AM 

Ph.D. Program in Data Science

Department of Computer, Control, and Management Engineering Antonio Ruberti (DIAG)

Sapienza University of Rome 

Room A6, Via Ariosto 25, Rome

SPEAKERS

Eleonora Grassucci

Assistant Professor

DIET@Sapienza

Maria Sofia Bucarelli

PhD Student in Data Science

DIAG@Sapienza

Giulia Cassarà

PhD Student in Data Science

DIAG@Sapienza

“The D&I@SoBigData.it event was organised as part of the SoBigData.it project (Prot. IR0000013 - Call n. 3264 of 12/28/2021) initiatives aimed at training new users and communities in the usage of the research infrastructure (SoBigData.eu).”

The course will make of use of research infrastructure of the sobigdata.it and sobigdata.eu project.

PROGRAM

10.00 Welcome address: Prof. Tiziana Catarci (Directress of DIAG-Sapienza

                                                          Prof. Fabrizio Silvestri (Chair of the Data Science Ph.D. Program)

10.10 On Generalization Bounds for Projective Clustering

Dr. Maria Sofia Bucarelli

Abstract: In this work, we explore clustering with points and subspaces as centers, considering how quickly solutions converge to optimal clustering. Notably, we achieve near-optimal convergence rates for both center-based objectives and subspace clustering, extending known bounds for k-means and k-median.

Joint work with Matilde Fjeldsø Larsen, Chris Schwiegelshohn, Mads Bech Toftrup

10.50  Sheaf Hypergraph Networks

Dr. Giulia Cassarà

Abstract: In this talk, she presents a collaborative research effort with Iulia Duta, Professor Fabrizio Silvestri, and Professor Pietro Liò on "Sheaf Hypergraph Networks." The paper introduces cellular sheaves to improve hypergraph representations, leading to a more expressive inductive bias than standard hypergraph diffusion. The authors developed two novel sheaf hypergraph Laplacians and used them to design two categories of models: Sheaf Hypergraph Neural Networks and Sheaf Hypergraph Convolutional Networks. These models significantly enhance performance on multiple benchmark datasets for hypergraph node classification.

Joint work with Iulia Duta, Fabrizio Silvestri, Pietro Liò

11.30  Generative Semantic Communication 

Dr. Eleonora Grassucci

Abstract: Semantic communication is poised to play a pivotal role in shaping the landscape of future AI-driven communication systems. Its challenge of extracting semantic information from the original complex content and regenerating semantically consistent data at the receiver, possibly being robust to channel corruptions, can be addressed with deep generative models. We will disclose the semantic communication challenges from the machine learning perspective and unveil how deep generative models will significantly enhance semantic communication frameworks in dealing with real-world complex data, extracting and exploiting semantic information, and being robust to channel corruptions. 

Joint work with Sergio Barbarossa, Danilo Comminiello

The event will include presentations and talks relevant for the sobigdata.it and sobigdata.eu initiative.

Zoom Meeting:  https://uniroma1.zoom.us/j/83672094716?pwd=OVFtTXRlZGJ2UElObldtOTNUVHRZZz09

(Meeting ID: 836 7209 4716 Passcode: 732175)