Mauro Bisson

30 papers receiving 349 citations

Peers

Mauro Bisson
Comparison fields: 5 of 61
  • Hardware and Architecture 94
  • Computational Mathematics 5
  • Computer Vision and Pattern Recognition 133
  • Computer Networks and Communications 97
  • Computational Mechanics 80
Replace H. Schröder with:
H. Schröder Germany
Tor Sørevik Norway
Helmar Burkhart Switzerland
Pedro Valero‐Lara Spain
Simon David Hammond United States
Pasqua D’Ambra Italy
J. Demmel United States
A. Kugel Germany
Ramachandran Vaidyanathan United States
Padma Raghavan United States
Mauro Bisson relative to H. Schröder Germany H. Schröder's profile →
Citations per field
00.5×9.2×
H. Schröder · 1×
Citations per year

Countries citing papers authored by Mauro Bisson

Since Specialization
Citations

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

Fields of papers citing papers by Mauro Bisson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mauro Bisson. 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 Mauro Bisson. The network helps show where Mauro Bisson may publish in the future.

Co-authors

The 25 scholars most cited alongside Mauro Bisson, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mauro Bisson Line = papers co-authored together Mauro Bisson links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201129
2 201727
3 201226
4 201326
5 201523
6 201520
7 201720
8 202019
9 201816
10 201615
11 201112
12 201210
13 201910
14 201210
15 201410
16 201510
17 20169
18 20119
19 20219
20 20119

About Mauro Bisson

Mauro Bisson is a scholar working on Hardware and Architecture, Computer Vision and Pattern Recognition, Computer Networks and Communications, Condensed Matter Physics and Artificial Intelligence, having authored 30 papers that have together received 359 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (11 papers), Graph Theory and Algorithms (9 papers), Theoretical and Computational Physics (7 papers), Advanced Data Storage Technologies (5 papers), Lattice Boltzmann Simulation Studies (4 papers), Advanced Graph Neural Networks (3 papers), Complex Network Analysis Techniques (3 papers) and Data Management and Algorithms (2 papers). The work is most often cited by research in Hardware and Architecture (94 citations), Computational Mathematics (5 citations), Computer Vision and Pattern Recognition (133 citations), Computer Networks and Communications (97 citations) and Computational Mechanics (80 citations). Mauro Bisson has collaborated with scholars based in United States, Italy and United Kingdom. Frequent co-authors include Massimiliano Fatica, Massimo Bernaschi, Simone Melchionna, Sauro Succi, D. Rossetti, Everett Phillips, Joshua Romero, Toshio Endo, Satoshi Matsuoka and Carlo Fantozzi. Their work appears in journals such as Computer Physics Communications, Journal of Parallel and Distributed Computing, IEEE Transactions on Parallel and Distributed Systems, Communications in Computational Physics and Physical Review Research.

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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