Valentina De Simone
- Computational Theory and Mathematics top 5%
- Numerical Analysis top 5%
- Computational Mechanics top 10%
- Management Science and Operations Research top 10%
- Atomic and Molecular Physics, and Optics
- Co-authors
- Daniela di SerafinoStefania CorsaroBenedetta MoriniStefania BellaviaA. MurliSonia CafieriLaura AntonelliMichele Ceccarelli
- Topics
- Sparse and Compressive Sensing Techniques (13 papers)Advanced Optimization Algorithms Research (12 papers)Matrix Theory and Algorithms (11 papers)
- Cited by
- Numerical AnalysisComputational Theory and MathematicsManagement Science and Operations Research
- Journals
- SHILAP Revista de lepidopterologíaSIAM Journal on Numerical AnalysisSIAM Review
In The Last Decade
Valentina De Simone
30 papers receiving 304 citations
Peers
Comparison fields: 5 of 59
- Computational Theory and Mathematics 129
- Numerical Analysis 122
- Computational Mechanics 96
- Management Science and Operations Research 67
- Atomic and Molecular Physics, and Optics 64
Countries citing papers authored by Valentina De Simone
This map shows the geographic impact of Valentina De Simone'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 Valentina De Simone with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Valentina De Simone more than expected).
Fields of papers citing papers by Valentina De Simone
This network shows the impact of papers produced by Valentina De Simone. 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 Valentina De Simone. The network helps show where Valentina De Simone may publish in the future.
Co-authorship network of co-authors of Valentina De Simone
This figure shows the co-authorship network connecting the top 25 collaborators of Valentina De Simone. A scholar is included among the top collaborators of Valentina De Simone 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 Valentina De Simone. Valentina De Simone is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 5 | |
| 5 | 4 | |
| 6 | 8 | |
| 7 | 7 | |
| 8 | 2 | |
| 9 | 19 | |
| 10 | 8 | |
| 11 | 24 | |
| 12 | 11 | |
| 13 | 23 | |
| 14 | 13 | |
| 15 | 4 | |
| 16 | 4 | |
| 17 | 18 | |
| 18 | 7 | |
| 19 | 21 | |
| 20 | 2 |
About Valentina De Simone
Valentina De Simone is a scholar working on Numerical Analysis, Computational Mechanics and Computational Theory and Mathematics, having authored 31 papers that have together received 316 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (13 papers), Advanced Optimization Algorithms Research (12 papers) and Matrix Theory and Algorithms (11 papers). The work is most often cited by research in Numerical Analysis (122 citations), Computational Theory and Mathematics (129 citations) and Management Science and Operations Research (67 citations). Valentina De Simone has collaborated with scholars based in Italy, China and Ireland. Frequent co-authors include Daniela di Serafino, Stefania Corsaro, Benedetta Morini, Stefania Bellavia, A. Murli, Sonia Cafieri, Laura Antonelli, Michele Ceccarelli, Gerardo Toraldo and Luisa D’Amore. Their work appears in journals such as SHILAP Revista de lepidopterología, SIAM Journal on Numerical Analysis and SIAM Review.
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.