Antonio Longa

I am Antonio Longa an Assistant Professor (RTD-A) at the University of Trento, actively engaged in research within the Structured Machine Learning (SML) Group led by Andrea Passerini. I earned my Ph.D. with honors from the University of Trento and Fondazione Bruno Kessler, under the mentorship of Bruno Lepri.

My academic journey has been marked by a deep-seated fascination with graphs. My Ph.D. research revolved around the intricate domain of mining temporal networks, where I explored the dynamic and evolving nature of complex systems.

I'm currently deeply engaged in my research, which spans the realms of Temporal Graph Neural Networks (TGNNs) and the vital domain of GNN explainability. My work involves unraveling the dynamics of temporal networks while also enhancing the interpretability of GNNs. These parallel endeavors allow me to explore the temporal dimension in machine learning while ensuring that the inner workings of GNNs are transparent and understandable.

I am always enthusiastic to talk about science, feel free to contact me :)


Publications

Meta-Path Learning for Multi-relational Graph Neural Networks
F. Ferrini, A. Longa, A. Passerini and M. Jaeger
Learning on Graphs 2023 (Oral)
2023
A Simple Latent Variable Model for Graph Learning and Inference
M. Jaeger, A. Longa, S. Azzolin, O. Schulte and A. Passerini
Learning on Graphs 2023
2023
Understanding Social Interactions via Temporal Network Analysis
A. Longa
Ph.D. Thesis
2023
Graph Neural Networks for temporal graphs: State of the art, open challenges, and opportunities
A. Longa, V. Lachi, G. Santin, M. Bianchini, B. Lepri, P. Liò, F. Scarselli and A. Passerini
TMLR 23
2023
Explaining the Explainers in Graph Neural Networks: a Comparative Study
A. Longa, S. Azzolin, G. Santin, G. Cencetti, P. Liò, B. Lepri and A. Passerini
[Under review ACM Computing surveys]
2022
Global Explainability of GNNs via Logic Combination of Learned Concepts
S. Azzolin, A. Longa, P. Barbiero, P. Liò and A. Passerini
ICLR 23
2022
Emotion Analysis Using Multilayered Networks for Graphical Representation of Tweets
A. Nguyen, A. Longa, M. Luca, J. Kaul and G. Lopez
IEEE access
2022
TEP-GNN: Accurate Execution Time Prediction of Functional Tests using Graph Neural Networks
H. P. Samoaa, A. Longa, M. Mohamad, M. H. Chehreghani and P. Leitner
PROFES22
2022
Generating fine-grained surrogate temporal networks
A. Longa, G. Cencetti, S. Lehmann, A. Passerini and B. Lepri
[Preprint]
2022
Generating Synthetic Mobility Networks with Generative Adversarial Networks
G. Mauro, M. Luca, A. Longa, B. Lepri and L. Pappalardo
EPJ Data Science
2022
An Efficient Procedure for Mining Egocentric Temporal Motifs
A. Longa, G. Cencetti, B. Lepri and A. Passerini
ECML PKDD DAMI
2021
Digital proximity tracing on empirical contact networks for pandemic control
G. Cencetti, G. Santin, A. Longa, E. Pigani, A. Barrat, C. Cattuto, S. Lehmann, M. Salathé and B. Lepri
Nature Communications
2021



Talks

MLG 23

Understanding how explainers work in graph neural networks
and
Global Explainability of GNNs via Logic Combination of Learned Concepts
(Abstract 1)
(Abstract 2)
September 22nd 2023
Torino, IT

NetSci 23

Graph Neural Networks for temporal graphs: State of the art, open challenges, and opportunities
Abstract
July 14th 2023
Vienna, Austria


Projects

Pytorch Geometric Tutorials

Collections of video tutorials and material for the implementation of GDL in PyG

Advanced Pytorch Geometric Tutorials

Collections of video tutorials and material for the implementation of advanced techniques in PyG

Egocentric Temporal Motifs Miner (ETMM)

Blog post presenting a novel mining technique based on the notion of Egocentric Temporal Motifs.

AI Trento Journal club

The AI Trento Journal Club is an open science initiative aiming to discuss and speculate about various topics of Machine Learning, Artificial Intelligence, and Computer Science.

LOG meetup Trento

Trento meetup of the Learning on Graph Conference, an annual research conference that covers areas broadly related to machine learning on graphs and geometry.


Teaching

Scientific Programming - Programming - 2023-2024

Master of Data Science - Trento University

Scientific Programming - Programming - 2022-2023

Master of Data Science - Trento University

Machine Learning - Module I - 2021 - 2022

Master of Science in Artificial Intelligence Systems - Trento University
Part 1 (Sklearn)

Machine Learning 2021 - 2022

Master of Science in Computer Science - Trento University
Part 1 (Sklearn) - Part 1 (Tensorflow)

Informatica 2020 - 2021

Scienze e Tecnologie Biomolecolari - Università degli Studi di Trento


Awards

  • Ph.D. intern at Cambridge University Economic support for three months of Ph.D. intern in UK.
  • Ph.D. scholarship extension: Three months extension of Ph.D. economic support.
  • NetSci2020 sponsorship: Economic support for the online conference of NetSci2020.
  • Ph.D. scholarship: Three year sponsorship, due to my fourth position among more than 120 participant.
  • Research support UK: Seven paid months in United Kingdom.
  • Erasmus plus: Five paid months at Aalto University, Finland.
  • National register of excellences: Obtained an award from the Italian Institute for School and Research, due to the design of a sustainable building for students.


Review

  • AAAI
  • IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
  • Transactions on Network Science and Engineering
  • ACM Computing survey
  • Physica A: Statistical Mechanics and its Applications