M. Pivanti
- Computational Mechanics top 10%
- Computer Vision and Pattern Recognition
- Computer Networks and Communications
- Electrical and Electronic Engineering
- Hardware and Architecture
- Co-authors
- Sebastiano Fabio SchifanoR. TripiccioneFilippo MantovaniAndrea ScagliariniFederico ToschiMauro SbragagliaLuca BiferaleP. Dalpiaz
- Topics
- Lattice Boltzmann Simulation Studies (10 papers)Generative Adversarial Networks and Image Synthesis (8 papers)Fluid Dynamics and Turbulent Flows (3 papers)
- Journals
- Computers & FluidsJournal of Physics Conference SeriesInstitutional Research Information System University of Ferrara (University of Ferrara)
- Partner nations
- ItalyGermanyNetherlands
In The Last Decade
M. Pivanti
15 papers receiving 103 citations
Peers
Comparison fields: 5 of 33
- Computational Mechanics 73
- Computer Vision and Pattern Recognition 51
- Computer Networks and Communications 43
- Electrical and Electronic Engineering 28
- Hardware and Architecture 22
Countries citing papers authored by M. Pivanti
This map shows the geographic impact of M. Pivanti'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 M. Pivanti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Pivanti more than expected).
Fields of papers citing papers by M. Pivanti
This network shows the impact of papers produced by M. Pivanti. 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 M. Pivanti. The network helps show where M. Pivanti may publish in the future.
Co-authorship network of co-authors of M. Pivanti
This figure shows the co-authorship network connecting the top 25 collaborators of M. Pivanti. A scholar is included among the top collaborators of M. Pivanti 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 M. Pivanti. M. Pivanti 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 | 2 | |
| 3 | 3 | |
| 4 | 4 | |
| 5 | 9 | |
| 6 | 25 | |
| 7 | 11 | |
| 8 | 3 | |
| 9 | 2 | |
| 10 | 16 | |
| 11 | 6 | |
| 12 | 1 | |
| 13 | 2 | |
| 14 | 11 | |
| 15 | 10 |
About M. Pivanti
M. Pivanti is a scholar working on Computational Mechanics, Health Information Management and Computer Vision and Pattern Recognition, having authored 15 papers that have together received 106 indexed citations. Recurring topics across this work include Lattice Boltzmann Simulation Studies (10 papers), Generative Adversarial Networks and Image Synthesis (8 papers) and Fluid Dynamics and Turbulent Flows (3 papers). The work is most often cited by research in Computational Mechanics (73 citations), Hardware and Architecture (22 citations) and Computer Vision and Pattern Recognition (51 citations). M. Pivanti has collaborated with scholars based in Italy, Germany and Netherlands. Frequent co-authors include Sebastiano Fabio Schifano, R. Tripiccione, Filippo Mantovani, Andrea Scagliarini, Federico Toschi, Mauro Sbragaglia, Luca Biferale, P. Dalpiaz, M. Sozzi and Massimo Gallerani. Their work appears in journals such as Computers & Fluids, Journal of Physics Conference Series and Institutional Research Information System University of Ferrara (University of Ferrara).
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.