collaborators

6 papers

cs.NI2026

Feasibility Assessment of Remote Driving via Latency Analysis of ITS-G5 and Cellular Networks in the MASA Living Lab

Gaetano Orazio Cauchi, Antonio Solida, Salvatore Iandolo +8

Remote driving has gained increasing attention as a key enabler for connected and automated vehicles. Yet its practical deployment hinges on wireless networks' ability to guarantee…

cs.LG2026

The Gaussian-Head OFL Family: One-Shot Federated Learning from Client Global Statistics

Fabio Turazza, Marco Picone, Marco Mamei

Classical Federated Learning relies on a multi-round iterative process of model exchange and aggregation between server and clients, with high communication costs and privacy risks…

cs.AI2026

Digital Twins & ZeroConf AI: Structuring Automated Intelligent Pipelines for Industrial Applications

Marco Picone, Fabio Turazza, Matteo Martinelli +1

The increasing complexity of Cyber-Physical Systems (CPS), particularly in the industrial domain, has amplified the challenges associated with the effective integration of Artifici…

cs.LG2026

Blockchain Federated Learning for Sustainable Retail: Reducing Waste through Collaborative Demand Forecasting

Fabio Turazza, Alessandro Neri, Marcello Pietri +3

Effective demand forecasting is crucial for reducing food waste. However, data privacy concerns often hinder collaboration among retailers, limiting the potential for improved pred…

cs.CR2026

FedBGS: A Blockchain Approach to Segment Gossip Learning in Decentralized Systems

Fabio Turazza, Marcello Pietri, Marco Picone +1

Privacy-Preserving Federated Learning (PPFL) is a Decentralized machine learning paradigm that enables multiple participants to collaboratively train a global model without sharing…

cs.DC2025

A Multi-Simulation Bridge for IoT Digital Twins

Marco Picone, Samuele Burattini, Marco Melloni +6

The increasing capabilities of Digital Twins (DTs) in the context of the Internet of Things (IoT) and Industrial IoT (IIoT) call for seamless integration with simulation platforms…