Gabriel Tanase
- Hardware and Architecture top 5%
- Computer Networks and Communications top 10%
- Computer Vision and Pattern Recognition top 10%
- Information Systems top 10%
- Artificial Intelligence
- Co-authors
- Lawrence RauchwergerNancy M. AmatoNathan ThomasMauro BiancoIoannis PapadopoulosOlga PearceCharles J ArcherGheorghe Almási
- Topics
- Parallel Computing and Optimization Techniques (10 papers)Distributed and Parallel Computing Systems (6 papers)Graph Theory and Algorithms (5 papers)
- Cited by
- Hardware and ArchitectureComputer Networks and CommunicationsComputer Vision and Pattern Recognition
- Journals
- ACM SIGPLAN NoticesConcurrency and Computation Practice and ExperienceInternational Journal of Parallel Programming
- Partner nations
- United StatesSaudi ArabiaCanada
In The Last Decade
Gabriel Tanase
14 papers receiving 193 citations
Peers
Comparison fields: 5 of 27
- Hardware and Architecture 143
- Computer Networks and Communications 134
- Computer Vision and Pattern Recognition 60
- Information Systems 55
- Artificial Intelligence 54
Countries citing papers authored by Gabriel Tanase
This map shows the geographic impact of Gabriel Tanase'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 Gabriel Tanase with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gabriel Tanase more than expected).
Fields of papers citing papers by Gabriel Tanase
This network shows the impact of papers produced by Gabriel Tanase. 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 Gabriel Tanase. The network helps show where Gabriel Tanase may publish in the future.
Co-authorship network of co-authors of Gabriel Tanase
This figure shows the co-authorship network connecting the top 25 collaborators of Gabriel Tanase. A scholar is included among the top collaborators of Gabriel Tanase 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 Gabriel Tanase. Gabriel Tanase is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 1 | |
| 3 | 5 | |
| 4 | 12 | |
| 5 | 7 | |
| 6 | 5 | |
| 7 | 7 | |
| 8 | 4 | |
| 9 | 3 | |
| 10 | 31 | |
| 11 | 41 | |
| 12 | 4 | |
| 13 | 7 | |
| 14 | 76 | |
| 15 | 5 |
About Gabriel Tanase
Gabriel Tanase is a scholar working on Hardware and Architecture, Computer Networks and Communications and Software, having authored 15 papers that have together received 211 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (10 papers), Distributed and Parallel Computing Systems (6 papers) and Graph Theory and Algorithms (5 papers). The work is most often cited by research in Hardware and Architecture (143 citations), Computer Networks and Communications (134 citations) and Computer Vision and Pattern Recognition (60 citations). Gabriel Tanase has collaborated with scholars based in United States, Saudi Arabia and Canada. Frequent co-authors include Lawrence Rauchwerger, Nancy M. Amato, Nathan Thomas, Mauro Bianco, Ioannis Papadopoulos, Olga Pearce, Charles J Archer, Gheorghe Almási, Joefon Jann and Pratap Pattnaik. Their work appears in journals such as ACM SIGPLAN Notices, Concurrency and Computation Practice and Experience and International Journal of Parallel Programming.
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.