Mariarosa Mazza
- Modeling and Simulation top 1%
- Fractional Differential Equations Solutions 16
- Numerical Analysis top 5%
- Differential Equations and Numerical Methods 8
- Numerical methods for differential equations 7
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- Matrix Theory and Algorithms 11
- Applied Mathematics top 5%
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- Numerical methods in engineering 9
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- Advanced Numerical Methods in Computational Mathematics 6
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- Image and Signal Denoising Methods 4
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- Electromagnetic Scattering and Analysis 4
Mariarosa Mazza
34 papers receiving 449 citations
Peers
Comparison fields: 5 of 39
- Modeling and Simulation 241
- Numerical Analysis 208
- Computational Theory and Mathematics 218
- Computational Mathematics 6
- Applied Mathematics 100
Countries citing papers authored by Mariarosa Mazza
This map shows the geographic impact of Mariarosa Mazza'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 Mariarosa Mazza with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mariarosa Mazza more than expected).
Fields of papers citing papers by Mariarosa Mazza
This network shows the impact of papers produced by Mariarosa Mazza. 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 Mariarosa Mazza. The network helps show where Mariarosa Mazza may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mariarosa Mazza, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 1 | |
| 2 | 2024 | 1 | |
| 3 | 2023 | 1 | |
| 4 | 2023 | 1 | |
| 5 | 2023 | 3 | |
| 6 | 2022 | 6 | |
| 7 | 2022 | 6 | |
| 8 | 2022 | 5 | |
| 9 | 2022 | 2 | |
| 10 | 2021 | 5 | |
| 11 | 2021 | 4 | |
| 12 | 2021 | 0 | |
| 13 | 2020 | 5 | |
| 14 | 2020 | 16 | |
| 15 | 2019 | 13 | |
| 16 | 2018 | 16 | |
| 17 | 2018 | 17 | |
| 18 | 2018 | 22 | |
| 19 | 2017 | 4 | |
| 20 | 2014 | 21 |
About Mariarosa Mazza
Mariarosa Mazza is a scholar working on Modeling and Simulation, Numerical Analysis, Applied Mathematics, Computational Theory and Mathematics and Mathematical Physics, having authored 35 papers that have together received 465 indexed citations. Recurring topics across this work include Fractional Differential Equations Solutions (16 papers), Matrix Theory and Algorithms (11 papers), Numerical methods in engineering (9 papers), Differential Equations and Numerical Methods (8 papers), Numerical methods for differential equations (7 papers), Advanced Numerical Methods in Computational Mathematics (6 papers), Image and Signal Denoising Methods (4 papers) and Electromagnetic Scattering and Analysis (4 papers). The work is most often cited by research in Modeling and Simulation (241 citations), Numerical Analysis (208 citations), Computational Theory and Mathematics (218 citations), Computational Mathematics (6 citations) and Applied Mathematics (100 citations). Mariarosa Mazza has collaborated with scholars based in Italy, Sweden and Germany. Frequent co-authors include Marco Donatelli, Stefano Serra‐Capizzano, Mehdi Dehghan, Carlo Garoni, Jennifer Pestana, Stefano De Marchı, Ahmed Ratnani, Francesco Dell’Accio, Rolf Krause and Leonardo Robol. Their work appears in journals such as Numerical Linear Algebra with Applications, Journal of Computational Physics, CALCOLO, Journal of Computational and Applied Mathematics and Computers & Mathematics with Applications.
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.