Paolo Frazzetto

I am a Postdoctoral Researcher at the Machine Learning Group of the University of Padova, Italy. Currently I am working in the SymboliG project within the Future of Artificial Intelligence (FAIR) group, where I am researching how to apply symbolic and domain knowledge for Generative AI.

During the PhD, I worked in AI Applications with Human Resources Data at Amajor SB S.p.a, under the supervision of Prof. Alessandro Sperduti within the Brain, Mind & Computer Science Doctoral School at the University of Padova.
I additionaly spent six month in Bielefeld, Germany, visitng the HammerLab. I have a broad interest in Statistical and Machine Learning, with a focus on techniques for structured data, and in particular Graph Neural Networks and Deepl Learning applied to natural and social sciences.

I am eager to advance my career in research, with a particular focus in postdoctoral and research scientist opportunities. I am actively seeking new positions, and I am available to relocate globally from September/October 2025.

Best way to reach out to me is via e-mail.

Publications

• Graph Neural Networks for Candidate-Job Matching: An Inductive Learning Approach
  Paolo Frazzetto, Muhammad Uzair Ul Haq, Flavia Fabris, Giovanni Da San Martino & Alessandro Sperduti
  Data Sci. Eng. (2025)
  DOI: 10.1007/s41019-025-00293-y
• Exact Computation of Any-Order Shapley Interactions for Graph Neural Networks
  Maximilian Muschalik, Fabian Fumagalli, Paolo Frazzetto, Eyke Hüllermeier, Barbara Hammer, Alessandro Sperduti
  ICLR 2025, The Thirteenth International Conference on Learning Representations
  View paper
• Leveraging Deep Learning in Human Resources: A Systematic Investigation of Graph Neural Networks for Candidate-Job Matching
  Ph.D. Thesis, submitted in December 2024, defended on March 26, 2025.
  Download
• From Text to Talent: A Pipeline for Extracting Insights from Candidate Profiles
  Paolo Frazzetto, Muhammad Uzair Ul Haq, Flavia Fabris, Alessandro Sperduti
  Presented at The 3rd Italian Conference on Big Data and Data Science (ITADATA), Pisa, Italy, 17-19 September 2024
  View paper
• Physics-Informed Graph Neural Cellular Automata: an Application to Compartmental Modelling
  Nicolò Navarin, Paolo Frazzetto, Luca Pasa, Pietro Verzelli, Filippo Visentin, Alessandro Sperduti, Cesare Alippi
  Accepted and presented at The International Joint Conference on Neural Networks (IJCNN), Yokohama, Japan, June 30 - July 5 2024
  View paper
• Beyond the Additive Nodes' Convolutions: a Study on High-Order Multiplicative Integration
  Paolo Frazzetto, Luca Pasa, Nicolò Navarin, Alessandro Sperduti
  Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing, 2024
  DOI: 10.1145/3605098.3636016
• Improving Soft Skill Extraction via Data Augmentation and Embedding Manipulation
  Muhammad Uzair Ul Haq, Paolo Frazzetto, Alessandro Sperduti, Giovanni Da San Martino
  Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing, 2024
  DOI: 10.1145/3605098.3636010
• Enhancing Human Resources through Data Science: a Case in Recruiting
  Paolo Frazzetto, Muhammad Uzair Ul Haq, Alessandro Sperduti
  The 2nd Italian Conference on Big Data and Data Science (ITADATA), Naples, Italy, 11-13 September, 2023
  View paper
• Topology preserving maps as aggregations for Graph Convolutional Neural Networks
  Paolo Frazzetto, Luca Pasa, Nicolò Navarin, Alessandro Sperduti
  Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 2023
  DOI: 10.1145/3555776.3577751

Curriculum Vitae

Download my complete curriculum vitae in PDF format:

Academia