Causal Inference over Time

Causal Inference over Time

By: Isacco Beretta
On: Causality, Fairness

Algorithmic Recourse (AR) addresses adverse outcomes in automated decision-making by offering actionable recommendations. However, current state-of...
Scalable Programming Models and Strategies for Efficient High-Performance Serverless in Hybrid and Heterogeneous Systems

Scalable Programming Models and Strategies for Efficient High-Performance Serverless in Hybrid an...

By: Valerio Besozzi
On: Cloud Computing, Serverless Computing, HPC

Developing a structured parallel programming model tailored for the serverless execution model.
Quantum Software Engineering

Quantum Software Engineering

By: Giuseppe Bisicchia
On: Quantum Computing, Software Engineering, Quantum Software Engineering

Quantum Computing, from a dream of a physicist, is now becoming a reality and promises to revolutionise the world. But, to best exploit the full po...
Explainable Federated Learning with Logic Explained Networks

Explainable Federated Learning with Logic Explained Networks

By: Valerio Bonsignori
On: XAI, Federated Learning

Poster is about an experimental framework for optimizing federated learning and proposing an adaptation of existing centralized technologies to imp...
Maximal Common Subsequences

Maximal Common Subsequences

By: Giovanni Buzzega
On: Algorithms on strings

In this poster we discuss the concept of inclusion-maximal subsequences of a set of strings. Subsequences do not have to be contiguous.
Is Generative AI Mature for Alnternative Image Descriptions of STEM Content?

Is Generative AI Mature for Alnternative Image Descriptions of STEM Content?

By: Marco Cardia
On: Accessibility in STEM

Artificial Intelligence (AI) supports visually impaired people in getting information about the world around them. This study investigates whether ...
Succint Trees and Trees Compression

Succint Trees and Trees Compression

By: Gabriel Carmona
On: Data Compression, Succint Data Structures, Tree Compression, Algorithms on Trees

Developing novel approaches for succinct tree data structures and efficient tree compression, and their applications.
Generate and ground LLM answers using external knowledge

Generate and ground LLM answers using external knowledge

By: Niko Dalla Noce
On: NLP, LLM, GNN, Knowledge Graphs

We present the research problem of retrieving accurate and contextually relevant information from structured documents.
Learning the Dynamics of Biological Networks with Deep Graph Networks

Learning the Dynamics of Biological Networks with Deep Graph Networks

By: Alessandro Dipalma
On: Computational Biology, Graph Machine Learning, Dynamical Systems

Large scale biological networks have expanded significantly due to advancements in high-throughput technologies, yet they remain static representat...
Non-fungible Mutable Token: Enabling and Protecting Mutability in NFTs

Non-fungible Mutable Token: Enabling and Protecting Mutability in NFTs

By: Francesco Donini
On: Blockchain, Distributed Systems, Security

“Traditional Non-Fungible Tokens (NFTs) are valuable for securely managing digital assets, uniquely identifying them, and enabling ownership transf...
Mobility Data Representations for Spatiotemporal Tasks

Mobility Data Representations for Spatiotemporal Tasks

By: Cristiano Landi
On: Mobility Data Science

Mobility data (MD) are everywhere. Smartphones and connected cars, as well as tracking devices with GPS capabilities, produce enormous amounts of s...
Self-learning based Decentralized Resource Management of Cloud Continuum

Self-learning based Decentralized Resource Management of Cloud Continuum

By: Lanpei Li
On: Cloud Computing, Resource Management, Distributed Computing, Machine Learning

This poster focuses on self-learning-based decentralized resource management in the Cloud Continuum, emphasizing the challenges and complexities of...
Approximate Nearest Neighbors Search over Neural Embeddings

Approximate Nearest Neighbors Search over Neural Embeddings

By: Silvio Martinico
On: LLMs, information retrieval, nearest neighbors search, algorithms

Similarity Search is a key search paradigm in our era. Large language models allows us to produce vectors representing data. Nearest Neighbors Sear...
ECLYPSE - Simplifying Cloud-Edge Simulations with Python

ECLYPSE - Simplifying Cloud-Edge Simulations with Python

By: Valerio De Caro, Jacopo Massa
On: Cloud Computing

ECLYPSE is a versatile Python-based platform designed for simulating and emulating complex Edge-Cloud environments, addressing key challenges in di...
Causal Models - Learning, Representation and Abstraction

Causal Models - Learning, Representation and Abstraction

By: Riccardo Massidda
On: Causality

Knowledge Representation in Reinforcement Learning

Knowledge Representation in Reinforcement Learning

By: Elia Piccoli
On: Reinforcement Learning

A common characteristic of modern Deep Learning approaches is that they involve training models “from scratch” to solve specific tasks. This approa...
Quantum Artificial Intelligence

Quantum Artificial Intelligence

By: Alessandro Poggiali
On: Quantum Computing

Hybrid Methods for Unsupervised Quantum Artificial Intelligence.
AI-based approaches for mobility data sharing and human dynamics understanding

AI-based approaches for mobility data sharing and human dynamics understanding

By: Chiara Pugliese
On: Mobility Data Mining

Our research aims to enhance mobility data sharing by developing AI-driven methods for creating, representing, and analyzing mobility data enriched...
A Causal Framework for Deferring Systems

A Causal Framework for Deferring Systems

By: Andrea Pugnana
On: Causality, Trustworthy AI, Human-Computer Interaction

The work bridges Learning to Defer (L2D) - an extension of supervised learning where the prediction task can be deferred to a human - and the causa...
Think Like a Vertex!

Think Like a Vertex!

By: Davide Rucci
On: Graph Algorithms, Distributed Computing, Combinatorics

We explore key challenges in graph problems, focusing on solutions using decentralized algorithms. We present the methodology to be used for develo...
Efficient Deep Learning on Graphs

Efficient Deep Learning on Graphs

By: Domenico Tortorella
On: Machine Learning on Graphs, Deep Neural Networks, Reservoir Computing

Graphs are an effective representation of entities and relations of many different objects such as chemical compounds, protein interaction networks...
End-User Development for Adaptive Social Robot

End-User Development for Adaptive Social Robot

By: Giacomo Vaiani
On: Human-Computer Interaction

This doctoral research explores the development of an End-User Development framework for adaptive social robots, focusing on enabling non-expert us...