G. Compostella
Impact in
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- Scientific Computing and Data Management
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- Distributed and Parallel Computing Systems
- Advanced Data Storage Technologies
- Peer-to-Peer Network Technologies
- Caching and Content Delivery
Papers in ⓘ
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- Advanced Data Storage Technologies 7
- Distributed and Parallel Computing Systems 7
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- Parallel Computing and Optimization Techniques 4
- Co-authors
- S. Pagan Griso (2 shared papers)I. Sfiligoi (3 shared papers)M. Potekhin (2 shared papers)V Fine (1 shared paper)K. De (2 shared papers)R. Walker (1 shared paper)T. Maeno (2 shared papers)A. R. Stradling (1 shared paper)
- Journals
- Journal of Physics Conference Series (6 papers)arXiv (Cornell University) (1 paper)2006 IEEE Nuclear Science Symposium Conference Record (1 paper)
- Partner nations
- ItalyUnited StatesGermany
In The Last Decade
G. Compostella
7 papers receiving 23 citations
Peers
Comparison fields: 5 of 9
- Information Systems and Management 9
- Computer Networks and Communications 22
- Hardware and Architecture 3
- Information Systems 7
- Nuclear and High Energy Physics 3
Countries citing papers authored by G. Compostella
This map shows the geographic impact of G. Compostella'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 G. Compostella with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites G. Compostella more than expected).
Fields of papers citing papers by G. Compostella
This network shows the impact of papers produced by G. Compostella. 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 G. Compostella. The network helps show where G. Compostella may publish in the future.
Co-authors
The 25 scholars most cited alongside G. Compostella, 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 | 2012 | 11 | |
| 2 | 2010 | 7 | |
| 3 | 2006 | 2 | |
| 4 | Optimizing traffic flow using quantum annealing and classical machine learning | 2017 | 1 |
| 5 | 2012 | 1 | |
| 6 | 2010 | 1 | |
| 7 | 2012 | 1 | |
| 8 | 2014 | 0 | |
| 9 | 2010 | 0 | |
| 10 | 2011 | 0 |
About G. Compostella
G. Compostella is a scholar working on Computer Networks and Communications, Hardware and Architecture, Nuclear and High Energy Physics, Information Systems and Management and Artificial Intelligence, having authored 10 papers that have together received 24 indexed citations. Recurring topics across this work include Advanced Data Storage Technologies (7 papers), Distributed and Parallel Computing Systems (7 papers), Parallel Computing and Optimization Techniques (4 papers), Particle physics theoretical and experimental studies (3 papers), Quantum Chromodynamics and Particle Interactions (2 papers), High-Energy Particle Collisions Research (2 papers), Quantum-Dot Cellular Automata (1 paper) and Quantum Computing Algorithms and Architecture (1 paper). The work is most often cited by research in Information Systems and Management (9 citations), Computer Networks and Communications (22 citations), Hardware and Architecture (3 citations), Information Systems (7 citations) and Nuclear and High Energy Physics (3 citations). G. Compostella has collaborated with scholars based in Italy, United States and Germany. Frequent co-authors include S. Pagan Griso, I. Sfiligoi, M. Potekhin, V Fine, K. De, R. Walker, T. Maeno, A. R. Stradling, D. Lucchesi and Douglas Thain. Their work appears in journals such as Journal of Physics Conference Series, arXiv (Cornell University) and 2006 IEEE Nuclear Science Symposium Conference Record.
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.