Mario Manzo
Impact in
- Artificial Intelligence top 5%
- Advanced Graph Neural Networks
- Imbalanced Data Classification Techniques
- Topic Modeling
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- Complex Network Analysis Techniques
Papers in
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- Advanced Graph Neural Networks 4
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- Bioinformatics and Genomic Networks 5
- Gene expression and cancer classification 4
- Co-authors
- Alessandro Rozza (3 shared papers)Antonio Maratea (7 shared papers)Alfredo Petrosino (4 shared papers)Mario Rosario Guarracino (7 shared papers)Lucia Maddalena (6 shared papers)Ilaria Granata (6 shared papers)Maurizio Giordano (5 shared papers)Ichcha Manipur (2 shared papers)
In The Last Decade
Mario Manzo
33 papers receiving 565 citations
Peers
Comparison fields: 5 of 102
- Artificial Intelligence 308
- Statistical and Nonlinear Physics 88
- Computer Vision and Pattern Recognition 128
- Media Technology 30
- Computational Mathematics 2
Countries citing papers authored by Mario Manzo
This map shows the geographic impact of Mario Manzo'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 Mario Manzo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mario Manzo more than expected).
Fields of papers citing papers by Mario Manzo
This network shows the impact of papers produced by Mario Manzo. 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 Mario Manzo. The network helps show where Mario Manzo may publish in the future.
Co-authors
The 22 scholars most cited alongside Mario Manzo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 261 | |
| 2 | 2013 | 112 | |
| 3 | 2020 | 24 | |
| 4 | 2021 | 22 | |
| 5 | 2021 | 18 | |
| 6 | 2021 | 17 | |
| 7 | 2019 | 11 | |
| 8 | 2019 | 10 | |
| 9 | 2020 | 9 | |
| 10 | 2014 | 9 | |
| 11 | 2020 | 7 | |
| 12 | 2022 | 6 | |
| 13 | 2022 | 6 | |
| 14 | 2023 | 5 | |
| 15 | 2020 | 5 | |
| 16 | 2012 | 5 | |
| 17 | 2017 | 5 | |
| 18 | 2016 | 5 | |
| 19 | 2021 | 5 | |
| 20 | 2019 | 4 |
About Mario Manzo
Mario Manzo is a scholar working on Artificial Intelligence, Molecular Biology, Computer Vision and Pattern Recognition, Computer Science Applications and Mechanical Engineering, having authored 33 papers that have together received 574 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (5 papers), Advanced Image and Video Retrieval Techniques (4 papers), Gene expression and cancer classification (4 papers), Advanced Graph Neural Networks (4 papers), Cellular and Composite Structures (4 papers), Mechanical Behavior of Composites (3 papers), Image Retrieval and Classification Techniques (3 papers) and Complex Network Analysis Techniques (3 papers). The work is most often cited by research in Artificial Intelligence (308 citations), Statistical and Nonlinear Physics (88 citations), Computer Vision and Pattern Recognition (128 citations), Media Technology (30 citations) and Computational Mathematics (2 citations). Mario Manzo has collaborated with scholars based in Italy, Russia and Germany. Frequent co-authors include Alessandro Rozza, Antonio Maratea, Alfredo Petrosino, Mario Rosario Guarracino, Lucia Maddalena, Ilaria Granata, Maurizio Giordano, Alfredo Petrosino, Ichcha Manipur and Donato Perfetto. Their work appears in journals such as IEEE/ACM Transactions on Computational Biology and Bioinformatics, Information Sciences, Macromolecular Symposia, International Journal of Human Capital and Information Technology Professionals and PLoS Computational Biology.
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.