Paolo Mignone, Ph.D., is an Associate Professor at Pegaso Telematic University, Department of Information Science and Technologies, Italy. He received his Ph.D. in Computer Science from the University of Bari Aldo Moro. His research focuses on machine learning, predictive modeling, transfer learning, multi-task learning, positive-unlabeled learning, anomaly detection, time series forecasting, and link prediction, with applications in bioinformatics, biomedical informatics, astroinformatics, digital forensics, environmental monitoring, and smart grid analytics. He has been involved in several national and international research projects and contracts on AI, symbiotic AI, smart grids, renewable energy systems, urban safety analytics, remote sensing, and bioinformatics, serving in roles such as Scientific Lead, Principal Investigator, and Researcher. His work has led to publications in leading international journals such as Bioinformatics, Machine Learning, IEEE Transactions on Human-Machine Systems, Big Data Research, Scientific Reports, Expert Systems with Applications, and Big Data, as well as in international conference proceedings. He has served in organizing, scientific, editorial, and program committee roles for international conferences and regularly reviews for international journals and conferences.

Research Interests

Machine Learning, Predictive Modeling, Transfer Learning, Multi-Task Learning, Positive-Unlabeled Learning, Anomaly Detection, Time Series Forecasting, Link Prediction

Paolo Mignone
PhD, Associate Professor
em@il: paolo.mignone @ unipegaso.it
webpage: https://p40l0m1gn0n3.github.io





Publications Legend

Journal Articles
Book
Conference or Workshop
Editorship
Collection
Other

Publications


2026
Paolo Mignone, Michele De Carolis:
Machine learning for the prioritization of Dyson sphere candidates. Expert Syst. Appl. 310: 131232 (2026)
DOI: https://doi.org/10.1016/j.eswa.2026.131232


2025
Antongiacomo Polimeno, Paolo Mignone, Chiara Braghin, Marco Anisetti, Michelangelo Ceci, Donato Malerba, Claudio A. Ardagna:
Balancing Protection and Quality in Big Data Analytics Pipelines. Big Data 13(2): 127-143 (2025)
DOI: https://doi.org/10.1089/big.2023.0065


2024
Paolo Mignone, Gianvito Pio, Michelangelo Ceci:
Distributed Heterogeneous Transfer Learning. Big Data Res. 37: 100456 (2024)
DOI: https://doi.org/10.1016/j.bdr.2024.100456
Paolo Mignone, Roberto Corizzo, Michelangelo Ceci:
Distributed and explainable GHSOM for anomaly detection in sensor networks. Mach. Learn. 113(7): 4445-4486 (2024)
DOI: https://doi.org/10.1007/s10994-023-06501-y


2023
Irena Koprinska, Paolo Mignone, Riccardo Guidotti, Szymon Jaroszewicz, Holger Fröning, Francesco Gullo, Pedro M. Ferreira, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk, João Gama, Rita P. Ribeiro, Ricard Gavaldà, Elio Masciari, Zbigniew W. Ras, Ettore Ritacco, Francesca Naretto, Andreas Theissler, Przemyslaw Biecek, Wouter Verbeke, Gregor Schiele, Franz Pernkopf, Michaela Blott, Ilaria Bordino, Ivan Luciano Danesi, Giovanni Ponti, Lorenzo Severini, Annalisa Appice, Giuseppina Andresini, Ibéria Medeiros, Guilherme Graça, Lee A. D. Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Diego Saldana Miranda, Konstantinos Sechidis, Arif Canakoglu, Sara Pidò, Pietro Pinoli, Albert Bifet, Sepideh Pashami:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part I PKDD/ECML Workshops (1) Communications in Computer and Information Science 1752, Springer (2023), ISBN: 978-3-031-23618-1
DOI: https://doi.org/10.1007/978-3-031-23618-1
Irena Koprinska, Paolo Mignone, Riccardo Guidotti, Szymon Jaroszewicz, Holger Fröning, Francesco Gullo, Pedro M. Ferreira, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk, João Gama, Rita P. Ribeiro, Ricard Gavaldà, Elio Masciari, Zbigniew W. Ras, Ettore Ritacco, Francesca Naretto, Andreas Theissler, Przemyslaw Biecek, Wouter Verbeke, Gregor Schiele, Franz Pernkopf, Michaela Blott, Ilaria Bordino, Ivan Luciano Danesi, Giovanni Ponti, Lorenzo Severini, Annalisa Appice, Giuseppina Andresini, Ibéria Medeiros, Guilherme Graça, Lee A. D. Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Diego Saldana Miranda, Konstantinos Sechidis, Arif Canakoglu, Sara Pidò, Pietro Pinoli, Albert Bifet, Sepideh Pashami:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part II PKDD/ECML Workshops (2) Communications in Computer and Information Science 1753, Springer (2023), ISBN: 978-3-031-23633-4
DOI: https://doi.org/10.1007/978-3-031-23633-4


2022
Paolo Mignone, Donato Malerba, Michelangelo Ceci:
Anomaly Detection for Public Transport and Air Pollution Analysis. IEEE Big Data: 2867-2874 (2022)
DOI: https://doi.org/10.1109/BigData55660.2022.10020470
Paolo Mignone, Gianvito Pio, Michelangelo Ceci:
Distributed Heterogeneous Transfer Learning for Link Prediction in the Positive Unlabeled Setting. IEEE Big Data: 5536-5541 (2022)
DOI: https://doi.org/10.1109/BigData55660.2022.10020270
Paolo Mignone, Donato Malerba, Michelangelo Ceci:
Anomaly Detection for Physical Threat Intelligence. itaDATA: 39-50 (2022)
DOI: https://ceur-ws.org/Vol-3340/paper38.pdf
Paolo Mignone, Gianvito Pio, Michelangelo Ceci:
Distributed Heterogeneous Transfer Learning. SEBD: 351-358 (2022)
DOI: https://ceur-ws.org/Vol-3194/paper42.pdf
Paolo Mignone, Donato Malerba, Michelangelo Ceci:
Anomaly Detection for Physical Threat Intelligence. PKDD/ECML Workshops (1): 281-292 (2022)
DOI: https://doi.org/10.1007/978-3-031-23618-1_20
Gianvito Pio, Paolo Mignone, Giuseppe Magazzù, Guido Zampieri, Michelangelo Ceci, Claudio Angione:
Integrating genome-scale metabolic modelling and transfer learning for human gene regulatory network reconstruction. Bioinform. 38(2): 487-493 (2022)
DOI: https://doi.org/10.1093/bioinformatics/btab647


2021
Daniela Mazzolini, Paolo Mignone, Patrizia Pavan, Gennaro Vessio:
An easy-to-explain decision support framework for forensic analysis of dynamic signatures. Digit. Investig. 38: 301216 (2021)
DOI: https://doi.org/10.1016/j.fsidi.2021.301216
Roberto Corizzo, Michelangelo Ceci, Gianvito Pio, Paolo Mignone, Nathalie Japkowicz:
Spatially-Aware Autoencoders for Detecting Contextual Anomalies in Geo-Distributed Data. DS: 461-471 (2021)
DOI: https://doi.org/10.1007/978-3-030-88942-5_36


2020
Michelangelo Ceci, Roberto Corizzo, Nathalie Japkowicz, Paolo Mignone, Gianvito Pio:
ECHAD: Embedding-Based Change Detection From Multivariate Time Series in Smart Grids. IEEE Access 8: 156053-156 (2020)
DOI: https://doi.org/10.1109/ACCESS.2020.3019095
Angelo Impedovo, Paolo Mignone, Corrado Loglisci, Michelangelo Ceci:
Simultaneous Process Drift Detection and Characterization with Pattern-Based Change Detectors. DS: 451-467 (2020)
DOI: https://doi.org/10.1007/978-3-030-61527-7_30
Paolo Mignone, Gianvito Pio, Domenica D'Elia, Michelangelo Ceci:
Exploiting transfer learning for the reconstruction of the human gene regulatory network. Bioinform. 36(5): 1553-1561 (2020)
DOI: https://doi.org/10.1093/bioinformatics/btz781


2019
Paolo Mignone, Gianvito Pio, Michelangelo Ceci:
Positive Unlabeled Link Prediction via Transfer Learning for Gene Network Reconstruction (Discussion Paper). SEBD (2019)
DOI: https://ceur-ws.org/Vol-2400/paper-06.pdf


2018
Paolo Mignone, Gianvito Pio:
Positive Unlabeled Link Prediction via Transfer Learning for Gene Network Reconstruction. ISMIS: 13-23 (2018)
DOI: https://doi.org/10.1007/978-3-030-01851-1_2


2015
Giuseppe Pirlo, Vito Cuccovillo, Moisés Díaz Cabrera, Donato Impedovo, Paolo Mignone:
Multidomain Verification of Dynamic Signatures Using Local Stability Analysis. IEEE Trans. Hum. Mach. Syst. 45(6): 805-810 (2015)
DOI: https://doi.org/10.1109/THMS.2015.2443050


2014
Giuseppe Pirlo, Vito Cuccovillo, Donato Impedovo, Paolo Mignone:
On-Line Signature Verification by Multi-domain Classification. ICFHR: 67-72 (2014)
DOI: https://doi.org/10.1109/ICFHR.2014.19