67 citations · 142 across the 14 of their papers we have counts for
14 papers
Longitudinal Multimodal Sensing of Physical Activity and Well-Being in Older Adults
Flavio Di Martino, Mattia G. Campana, Marcello Magno +2
Wearable and mobile sensing technologies enable continuous monitoring of human behavior and health in real-world settings. However, predictive modeling in longitudinal multimodal d…
FedSub: Introducing Class-aware Subnetworks Fusion to Enhance Personalized Federated Learning
Mattia Giovanni Campana, Franca Delmastro
Personalized Federated Learning aims at addressing the challenges of non-IID data in collaborative model training. However, existing methods struggle to balance personalization and…
ContextLabeler Dataset: physical and virtual sensors data collected from smartphone usage in-the-wild
Mattia Giovanni Campana, Franca Delmastro
This paper describes a data collection campaign and the resulting dataset derived from smartphone sensors characterizing the daily life activities of 3 volunteers in a period of tw…
A Machine-Learned Ranking Algorithm for Dynamic and Personalised Car Pooling Services
Mattia Giovanni Campana, Franca Delmastro, Raffaele Bruno
Car pooling is expected to significantly help in reducing traffic congestion and pollution in cities by enabling drivers to share their cars with travellers with similar itinerarie…
Context-Aware Configuration and Management of WiFi Direct Groups for Real Opportunistic Networks
Valerio Arnaboldi, Mattia Giovanni Campana, Franca Delmastro
Wi-Fi Direct is a promising technology for the support of device-to-device communications (D2D) on commercial mobile devices. However, the standard as-it-is is not sufficient to su…
PLIERS: a Popularity-Based Recommender System for Content Dissemination in Online Social Networks
Valerio Arnaboldi, Mattia Giovanni Campana, Franca Delmastro +1
In this paper, we propose a novel tag-based recommender system called PLIERS, which relies on the assumption that users are mainly interested in items and tags with similar popular…
Recommender Systems for Online and Mobile Social Networks: A survey
Mattia Giovanni Campana, Franca Delmastro
Recommender Systems (RS) currently represent a fundamental tool in online services, especially with the advent of Online Social Networks (OSN). In this case, users generate huge am…
Lightweight Modeling of User Context Combining Physical and Virtual Sensor Data
Mattia Giovanni Campana, Dimitris Chatzopoulos, Franca Delmastro +1
The multitude of data generated by sensors available on users' mobile devices, combined with advances in machine learning techniques, support context-aware services in recognizing…
MyDigitalFootprint: an extensive context dataset for pervasive computing applications at the edge
Mattia Giovanni Campana, Franca Delmastro
The widespread diffusion of connected smart devices has contributed to the rapid expansion and evolution of the Internet at its edge. Personal mobile devices interact with other sm…
COMPASS: Unsupervised and Online Clustering of Complex Human Activities from Smartphone Sensors
Mattia Giovanni Campana, Franca Delmastro
Modern mobile devices are able to provide context-aware and personalized services to the users, by leveraging on their sensing capabilities to infer the activity and situation in w…
A Transfer Learning and Explainable Solution to Detect mpox from Smartphones images
Mattia Giovanni Campana, Marco Colussi, Franca Delmastro +2
In recent months, the monkeypox (mpox) virus -- previously endemic in a limited area of the world -- has started spreading in multiple countries until being declared a ``public hea…
A Personalized Recommender System for Pervasive Social Networks
Valerio Arnaboldi, Mattia G. Campana, Franca Delmastro +1
The current availability of interconnected portable devices, and the advent of the Web 2.0, raise the problem of supporting anywhere and anytime access to a huge amount of content,…
L3-Net Deep Audio Embeddings to Improve COVID-19 Detection from Smartphone Data
Mattia Giovanni Campana, Andrea Rovati, Franca Delmastro +1
Smartphones and wearable devices, along with Artificial Intelligence, can represent a game-changer in the pandemic control, by implementing low-cost and pervasive solutions to reco…
On-device modeling of user's social context and familiar places from smartphone-embedded sensor data
Mattia Giovanni Campana, Franca Delmastro
Context modeling and recognition represent complex tasks that allow mobile and ubiquitous computing applications to adapt to the user's situation. Current solutions mainly focus on…