D. Brian Larkins
- Computer Networks and Communications top 5%
- Hardware and Architecture top 5%
- Information Systems top 5%
- Artificial Intelligence
- Computer Science Applications top 10%
- Co-authors
- James DinanP. SadayappanSriram KrishnamoorthyJarek NieplochaLouis J. RubboJames C. MooreAtanas RountevSrinivasan Parthasarathy
- Topics
- Parallel Computing and Optimization Techniques (10 papers)Advanced Data Storage Technologies (7 papers)Teaching and Learning Programming (5 papers)
- Journals
- IEEE International Conference on High Performance Computing, Data, and AnalyticsProcedia Computer ScienceJournal of computing sciences in colleges
- Partner nations
- United States
In The Last Decade
D. Brian Larkins
17 papers receiving 281 citations
Peers
Comparison fields: 5 of 47
- Computer Networks and Communications 203
- Hardware and Architecture 181
- Information Systems 114
- Artificial Intelligence 36
- Computer Science Applications 34
Countries citing papers authored by D. Brian Larkins
This map shows the geographic impact of D. Brian Larkins'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 D. Brian Larkins with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D. Brian Larkins more than expected).
Fields of papers citing papers by D. Brian Larkins
This network shows the impact of papers produced by D. Brian Larkins. 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 D. Brian Larkins. The network helps show where D. Brian Larkins may publish in the future.
Co-authorship network of co-authors of D. Brian Larkins
This figure shows the co-authorship network connecting the top 25 collaborators of D. Brian Larkins. A scholar is included among the top collaborators of D. Brian Larkins 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 D. Brian Larkins. D. Brian Larkins is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 3 | |
| 3 | 5 | |
| 4 | 3 | |
| 5 | 2 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 25 | |
| 10 | 2 | |
| 11 | 1 | |
| 12 | 2 | |
| 13 | 2 | |
| 14 | Efficient run-time support for global view programming of linked data structures on distributed memory parallel systems | 1 |
| 15 | 16 | |
| 16 | 172 | |
| 17 | 5 | |
| 18 | 44 | |
| 19 | 5 |
About D. Brian Larkins
D. Brian Larkins is a scholar working on Hardware and Architecture, Computer Science Applications and Media Technology, having authored 19 papers that have together received 292 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (10 papers), Advanced Data Storage Technologies (7 papers) and Teaching and Learning Programming (5 papers). The work is most often cited by research in Hardware and Architecture (181 citations), Computer Networks and Communications (203 citations) and Computer Science Applications (34 citations). D. Brian Larkins has collaborated with scholars based in United States. Frequent co-authors include James Dinan, P. Sadayappan, Sriram Krishnamoorthy, Jarek Nieplocha, Louis J. Rubbo, James C. Moore, Atanas Rountev, Srinivasan Parthasarathy, William M. Jones and Philip Roberts. Their work appears in journals such as IEEE International Conference on High Performance Computing, Data, and Analytics, Procedia Computer Science and Journal of computing sciences in colleges.
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.