Edoardo Prezioso

484 total citations
23 papers, 298 citations indexed

About

Edoardo Prezioso is a scholar working on Artificial Intelligence, Signal Processing and Management Science and Operations Research. According to data from OpenAlex, Edoardo Prezioso has authored 23 papers receiving a total of 298 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 4 papers in Signal Processing and 4 papers in Management Science and Operations Research. Recurrent topics in Edoardo Prezioso's work include Traffic Prediction and Management Techniques (4 papers), Stock Market Forecasting Methods (3 papers) and Time Series Analysis and Forecasting (3 papers). Edoardo Prezioso is often cited by papers focused on Traffic Prediction and Management Techniques (4 papers), Stock Market Forecasting Methods (3 papers) and Time Series Analysis and Forecasting (3 papers). Edoardo Prezioso collaborates with scholars based in Italy, China and Lithuania. Edoardo Prezioso's co-authors include Fabio Giampaolo, Francesco Piccialli, Gang Mei, Salvatore Cuomo, Nengxiong Xu, Zhongjian Zhang, Zhengjing Ma, Giovanni Acampora, David Camacho and Diletta Chiaro and has published in prestigious journals such as Scientific Reports, IEEE Internet of Things Journal and Information Fusion.

In The Last Decade

Edoardo Prezioso

23 papers receiving 287 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Edoardo Prezioso Italy 9 115 41 33 33 31 23 298
Zerina Mašetić Bosnia and Herzegovina 8 114 1.0× 16 0.4× 47 1.4× 27 0.8× 14 0.5× 17 456
Tobias Pielok Germany 2 135 1.2× 18 0.4× 21 0.6× 14 0.4× 8 0.3× 2 434
Yasser A. Ali Saudi Arabia 10 83 0.7× 29 0.7× 18 0.5× 14 0.4× 8 0.3× 26 428
Raghvendra Kumar India 11 65 0.6× 24 0.6× 65 2.0× 18 0.5× 96 3.1× 31 527
King Ma Canada 4 109 0.9× 40 1.0× 13 0.4× 71 2.2× 6 0.2× 11 348
Vatsal Patel India 4 72 0.6× 13 0.3× 20 0.6× 19 0.6× 8 0.3× 9 312
Alaknanda Ashok India 12 105 0.9× 8 0.2× 28 0.8× 33 1.0× 17 0.5× 47 430
Adriaan Brebels Russia 4 88 0.8× 42 1.0× 16 0.5× 33 1.0× 5 0.2× 8 364
Wanan Liu China 11 192 1.7× 65 1.6× 9 0.3× 19 0.6× 8 0.3× 15 549
Hongjie Chen China 11 161 1.4× 11 0.3× 22 0.7× 73 2.2× 175 5.6× 30 453

Countries citing papers authored by Edoardo Prezioso

Since Specialization
Citations

This map shows the geographic impact of Edoardo Prezioso's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Edoardo Prezioso with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Edoardo Prezioso more than expected).

Fields of papers citing papers by Edoardo Prezioso

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Edoardo Prezioso. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Edoardo Prezioso. The network helps show where Edoardo Prezioso may publish in the future.

Co-authorship network of co-authors of Edoardo Prezioso

This figure shows the co-authorship network connecting the top 25 collaborators of Edoardo Prezioso. A scholar is included among the top collaborators of Edoardo Prezioso based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Edoardo Prezioso. Edoardo Prezioso is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Prezioso, Edoardo, et al.. (2024). Leveraging Digital Twins and Generative AI for Effective Urban Mobility Management. 146–153. 3 indexed citations
2.
Aceto, Giuseppe, Fabio Giampaolo, Stefano Izzo, et al.. (2024). Synthetic and privacy-preserving traffic trace generation using generative AI models for training Network Intrusion Detection Systems. Journal of Network and Computer Applications. 229. 103926–103926. 7 indexed citations
3.
Savoia, Marcella, et al.. (2024). Eco-FL: Enhancing Federated Learning sustainability in edge computing through energy-efficient client selection. Computer Communications. 225. 156–170. 6 indexed citations
4.
Giampaolo, Fabio, Stefano Izzo, Edoardo Prezioso, et al.. (2023). A Privacy Preserving Service-Oriented Approach for Data Anonymization Through Deep Learning. 12. 738–746. 1 indexed citations
5.
Chiaro, Diletta, et al.. (2023). The Impact of Adversarial Attacks on Interpretable Semantic Segmentation in Cyber–Physical Systems. IEEE Systems Journal. 1–8. 7 indexed citations
6.
Cola, Vincenzo Schiano Di, Diletta Chiaro, Edoardo Prezioso, Stefano Izzo, & Fabio Giampaolo. (2023). Insight Extraction From E-Health Bookings by Means of Hypergraph and Machine Learning. IEEE Journal of Biomedical and Health Informatics. 27(10). 4649–4659. 4 indexed citations
7.
Giampaolo, Fabio, Edoardo Prezioso, Salvatore Cuomo, et al.. (2023). ENCODE - Ensemble neural combination for optimal dimensionality encoding in time-series forecasting. Information Fusion. 100. 101918–101918. 8 indexed citations
8.
Chiaro, Diletta, Edoardo Prezioso, Michele Ianni, & Fabio Giampaolo. (2023). FL-Enhance: A federated learning framework for balancing non-IID data with augmented and shared compressed samples. Information Fusion. 98. 101836–101836. 21 indexed citations
9.
Prezioso, Edoardo, Fabio Giampaolo, Stefano Izzo, Marcella Savoia, & Francesco Piccialli. (2023). Integrating Object Detection and Advanced Analytics for Smart City Crowd Management. 1–6. 2 indexed citations
10.
Giampaolo, Fabio, Stefano Izzo, Edoardo Prezioso, & Francesco Piccialli. (2023). Investigating Random Variations of the Forward-Forward Algorithm for Training Neural Networks. 1–7. 1 indexed citations
11.
Piccialli, Francesco, Fabio Giampaolo, Vincenzo Schiano Di Cola, et al.. (2022). A machine learning-based approach for mercury detection in marine waters. 1–10. 1 indexed citations
12.
Peng, Kai, et al.. (2022). Mobility and Privacy-Aware Offloading of AR Applications for Healthcare Cyber-Physical Systems in Edge Computing. IEEE Transactions on Network Science and Engineering. 10(5). 2662–2673. 17 indexed citations
13.
Giampaolo, Fabio, et al.. (2022). Neural networks generative models for time series. Journal of King Saud University - Computer and Information Sciences. 34(10). 7920–7939. 16 indexed citations
14.
Ma, Zhengjing, Gang Mei, Edoardo Prezioso, Zhongjian Zhang, & Nengxiong Xu. (2021). A deep learning approach using graph convolutional networks for slope deformation prediction based on time-series displacement data. Neural Computing and Applications. 33(21). 14441–14457. 49 indexed citations
15.
Piccialli, Francesco, Francesco Calabrò, Salvatore Cuomo, et al.. (2021). Precision medicine and machine learning towards the prediction of the outcome of potential celiac disease. Scientific Reports. 11(1). 5683–5683. 23 indexed citations
16.
Piccialli, Francesco, Fabio Giampaolo, Edoardo Prezioso, David Camacho, & Giovanni Acampora. (2021). Artificial intelligence and healthcare: Forecasting of medical bookings through multi-source time-series fusion. Information Fusion. 74. 1–16. 44 indexed citations
17.
Piccialli, Francesco, et al.. (2021). Predictive Analytics for Smart Parking: A Deep Learning Approach in Forecasting of IoT Data. ACM Transactions on Internet Technology. 21(3). 1–21. 33 indexed citations
18.
Prezioso, Edoardo, et al.. (2021). Machine Learning Insights for Behavioral Data Analysis Supporting the Autonomous Vehicles Scenario. IEEE Internet of Things Journal. 10(4). 3107–3117. 8 indexed citations
19.
Piccialli, Francesco, et al.. (2020). A deep learning approach for facility patient attendance prediction based on medical booking data. Scientific Reports. 10(1). 14623–14623. 8 indexed citations
20.
Piccialli, Francesco, et al.. (2020). Unsupervised learning on multimedia data: a Cultural Heritage case study. Multimedia Tools and Applications. 79(45-46). 34429–34442. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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