Nicola Prezza
Impact in
- Hardware and Architecture top 10%
- Network Packet Processing and Optimization
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- semigroups and automata theory
- Cellular Automata and Applications
Papers in
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- semigroups and automata theory 24
- Cellular Automata and Applications 11
- Computability, Logic, AI Algorithms 3
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- Algorithms and Data Compression 44
- Natural Language Processing Techniques 8
- Co-authors
- Alberto Policriti (14 shared papers)Dominik Kempa (2 shared papers)Gonzalo Navarro (8 shared papers)Travis Gagie (8 shared papers)Giovanna Rosone (6 shared papers)Marinella Sciortino (5 shared papers)Francesco Vezzi (3 shared papers)Mathieu Raffinot (2 shared papers)
In The Last Decade
Nicola Prezza
49 papers receiving 399 citations
Peers
Comparison fields: 5 of 44
- Hardware and Architecture 75
- Computational Theory and Mathematics 170
- Artificial Intelligence 317
- Computer Graphics and Computer-Aided Design 9
- Molecular Biology 145
Countries citing papers authored by Nicola Prezza
This map shows the geographic impact of Nicola Prezza'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 Nicola Prezza with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicola Prezza more than expected).
Fields of papers citing papers by Nicola Prezza
This network shows the impact of papers produced by Nicola Prezza. 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 Nicola Prezza. The network helps show where Nicola Prezza may publish in the future.
Co-authors
The 25 scholars most cited alongside Nicola Prezza, 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 53 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 60 | |
| 2 | 2015 | 37 | |
| 3 | 2016 | 29 | |
| 4 | 2018 | 22 | |
| 5 | 2017 | 20 | |
| 6 | 2022 | 20 | |
| 7 | 2019 | 19 | |
| 8 | 2012 | 18 | |
| 9 | 2020 | 17 | |
| 10 | 2018 | 12 | |
| 11 | 2021 | 11 | |
| 12 | 2017 | 10 | |
| 13 | 2021 | 9 | |
| 14 | 2020 | 9 | |
| 15 | 2020 | 9 | |
| 16 | 2015 | 9 | |
| 17 | 2017 | 8 | |
| 18 | 2016 | 8 | |
| 19 | 2018 | 6 | |
| 20 | 2014 | 5 |
About Nicola Prezza
Nicola Prezza is a scholar working on Computational Theory and Mathematics, Artificial Intelligence, Hardware and Architecture, Molecular Biology and Computer Vision and Pattern Recognition, having authored 53 papers that have together received 407 indexed citations. Recurring topics across this work include Algorithms and Data Compression (44 papers), semigroups and automata theory (24 papers), DNA and Biological Computing (14 papers), Cellular Automata and Applications (11 papers), Network Packet Processing and Optimization (9 papers), Natural Language Processing Techniques (8 papers), Genomics and Phylogenetic Studies (3 papers) and Computability, Logic, AI Algorithms (3 papers). The work is most often cited by research in Hardware and Architecture (75 citations), Computational Theory and Mathematics (170 citations), Artificial Intelligence (317 citations), Computer Graphics and Computer-Aided Design (9 citations) and Molecular Biology (145 citations). Nicola Prezza has collaborated with scholars based in Italy, Denmark and Chile. Frequent co-authors include Alberto Policriti, Dominik Kempa, Gonzalo Navarro, Travis Gagie, Giovanna Rosone, Marinella Sciortino, Francesco Vezzi, Mathieu Raffinot, Fabio Cunial and Tomasz Kociumaka. Their work appears in journals such as BMC Bioinformatics, Algorithms for Molecular Biology, Lecture notes in computer science, Archives of Toxicology and Information and Computation.
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.