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 Relational Deep Learning.

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

I am currently seeking new opportunities in both academia and industry.


Publications

Explaining the Explainers in Graph Neural Networks: a Comparative Study A. Longa, S. Azzolin, G. Santin, G. Cencetti, P. Liò, B. Lepri, A. Passerini
ACM Computing Surveys 2024
Patterns in temporal networks with higher-order egocentric structures B. Arregui-Garcia, A. Longa, Q.F. Lotito, S. Meloni, G. Cencetti
Entropy 2024
Putting Context in Context: the Impact of Discussion Structure on Text Classification N. Penzo, A. Longa, B. Lepri, S. Tonelli, M. Guerrini
EACL 2024 2024
Generating Fine-Grained Surrogate Temporal Networks A. Longa, G. Cencetti, S. Lehmann, A. Passerini, B. Lepri
Communications Physics 2024
A Simple and Expressive Graph Neural Network Based Method for Structural Link Representation V. Lachi, F. Ferrini, A. Longa, B. Lepri, A. Passerini
ICML 2024 Workshop GRaM 2024
Sheaf Diffusion Goes Nonlinear: Enhancing GNNs with Adaptive Sheaf Laplacians O. Zaghen, A. Longa, S. Azzolin, L. Telyatnikov, A. Passerini, P. Liò
ICML 2024 Workshop GRaM 2024
A unified active learning framework for annotating graph data for regression task P. Samoaa, L. Aronsson, A. Longa, P. Leitner, M.H. Chehregnani
Engineering Applications of Artificial Intelligence 2024
Meta-Path Learning for Multi-relational Graph Neural Networks F. Ferrini, A. Longa, A. Passerini, 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, 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, Challenges, and Opportunities A. Longa, V. Lachi, G. Santin, M. Bianchini, B. Lepri, P. Liò, F. Scarselli, A. Passerini
TMLR 2023 2023
Global Explainability of GNNs via Logic Combination of Learned Concepts S. Azzolin, A. Longa, P. Barbiero, P. Liò, A. Passerini
ICLR 2023 2022
Emotion Analysis Using Multilayered Networks for Graphical Representation of Tweets A. Nguyen, A. Longa, M. Luca, J. Kaul, 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, P. Leitner
PROFES 2022 2022
Generating Synthetic Mobility Networks with Generative Adversarial Networks G. Mauro, M. Luca, A. Longa, B. Lepri, L. Pappalardo
EPJ Data Science 2022
An Efficient Procedure for Mining Egocentric Temporal Motifs A. Longa, G. Cencetti, B. Lepri, A. Passerini
ECML PKDD DAMI 2022
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, B. Lepri
Nature Communications 2021


Talks


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 - 2024-2025

Master of Data Science - Trento University

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

  • NeurIPS
  • TMLR
  • LOG
  • 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