Jay Alameda

31 papers receiving 459 citations

Peers

Jay Alameda
Comparison fields: 5 of 105
  • Information Systems and Management 195
  • Computer Networks and Communications 239
  • Hardware and Architecture 41
  • Information Systems 90
  • Geology 15
Replace Jakub Mościcki with:
Jakub Mościcki Switzerland
Joris Borgdorff Netherlands
Suresh Marru United States
Kerstin Kleese van Dam United States
Wes Bethel United States
Nathan Fabian United States
Alessandro Costantini Italy
Tomasz Gubała Poland
Roselyne Tchoua United States
Daniele Cesini Italy
Jay Alameda relative to Jakub Mościcki Switzerland Jakub Mościcki's profile →
Citations per field
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Jakub Mościcki · 1×
Citations per year

Countries citing papers authored by Jay Alameda

Since Specialization
Citations

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

Fields of papers citing papers by Jay Alameda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jay Alameda, 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 Jay Alameda Line = papers co-authored together Jay Alameda links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200656
2 200448
3 200540
4 200539
5 200539
6 200138
7 199135
8
Hydroinformatics: Data Integrative Approaches in Computation, Analysis, and Modeling
200530
9 201627
10 200220
11 198919
12 201515
13
Proceedings of the 2014 Annual Conference on Extreme Science and Engineering Discovery Environment
201414
14 199310
15 200210
16 19979
17 20186
18 20145
19 20164
20 20054

About Jay Alameda

Jay Alameda is a scholar working on Computer Networks and Communications, Information Systems and Management, Information Systems, Hardware and Architecture and Artificial Intelligence, having authored 31 papers that have together received 492 indexed citations. Recurring topics across this work include Distributed and Parallel Computing Systems (16 papers), Scientific Computing and Data Management (14 papers), Parallel Computing and Optimization Techniques (7 papers), Research Data Management Practices (5 papers), Advanced MRI Techniques and Applications (3 papers), Environmental Monitoring and Data Management (3 papers), NMR spectroscopy and applications (2 papers) and Cloud Computing and Resource Management (2 papers). The work is most often cited by research in Information Systems and Management (195 citations), Computer Networks and Communications (239 citations), Hardware and Architecture (41 citations), Information Systems (90 citations) and Geology (15 citations). Jay Alameda has collaborated with scholars based in United States, Bulgaria and Serbia. Frequent co-authors include Dennis Gannon, Richard C. Alkire, Timothy O. Drews, Richard D. Braatz, Eric G. Webb, Richard L. Magin, Harold M. Swartz, Beth Plale, Marlon Pierce and Aleksander Slominski. Their work appears in journals such as Magnetic Resonance in Medicine, Proceedings of the IEEE, IBM Journal of Research and Development, Magnetic Resonance Imaging and AIChE Journal.

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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