Pasqua D’Ambra

484 total citations
42 papers, 257 citations indexed

About

Pasqua D’Ambra is a scholar working on Computational Theory and Mathematics, Computational Mechanics and Hardware and Architecture. According to data from OpenAlex, Pasqua D’Ambra has authored 42 papers receiving a total of 257 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computational Theory and Mathematics, 12 papers in Computational Mechanics and 7 papers in Hardware and Architecture. Recurrent topics in Pasqua D’Ambra's work include Matrix Theory and Algorithms (12 papers), Advanced Numerical Methods in Computational Mathematics (8 papers) and Parallel Computing and Optimization Techniques (7 papers). Pasqua D’Ambra is often cited by papers focused on Matrix Theory and Algorithms (12 papers), Advanced Numerical Methods in Computational Mathematics (8 papers) and Parallel Computing and Optimization Techniques (7 papers). Pasqua D’Ambra collaborates with scholars based in Italy, United States and United Kingdom. Pasqua D’Ambra's co-authors include Salvatore Filippone, Daniela di Serafino, Panayot S. Vassilevski, Mario Rosario Guarracino, Domenico Talia, Gaetano Tartaglione, Giulio Giunta, Alfredo Buttari, Marco Danelutto and Angelo Riccio and has published in prestigious journals such as Annals of the New York Academy of Sciences, SAE technical papers on CD-ROM/SAE technical paper series and Environmental Modelling & Software.

In The Last Decade

Pasqua D’Ambra

40 papers receiving 250 citations

Peers

Pasqua D’Ambra
Comparison fields: 5 of 58
  • Computational Theory and Mathematics 98
  • Computational Mechanics 92
  • Hardware and Architecture 81
  • Computer Networks and Communications 69
  • Atomic and Molecular Physics, and Optics 28
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Citations per field, relative to Pasqua D’Ambra
Pasqua D’Ambra · 1×
Citations per year, relative to Pasqua D’Ambra
Pasqua D’Ambra · 1×

Countries citing papers authored by Pasqua D’Ambra

Since Specialization
Citations

This map shows the geographic impact of Pasqua D’Ambra'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 Pasqua D’Ambra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pasqua D’Ambra more than expected).

Fields of papers citing papers by Pasqua D’Ambra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pasqua D’Ambra. 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 Pasqua D’Ambra. The network helps show where Pasqua D’Ambra may publish in the future.

Co-authorship network of co-authors of Pasqua D’Ambra

This figure shows the co-authorship network connecting the top 25 collaborators of Pasqua D’Ambra. A scholar is included among the top collaborators of Pasqua D’Ambra 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 Pasqua D’Ambra. Pasqua D’Ambra 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
# Work Indexed citations
1 1
2 1
3 1
4 1
5 10
6 2
7 0
8 19
9 11
10 8
11 5
12 2
13
Proceedings of the 2011 international conference on Parallel Processing - Volume 2
3
14
Euro-Par 2010 parallel processing : 16th International Euro-Par Conference, Ischia, Italy, August 31 - September 3, 2010 : proceedings
1
15 21
16 4
17 16
18 4
19 1
20 2

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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