Ester M. Garzón

72 papers receiving 960 citations

Peers

Ester M. Garzón
Comparison fields: 5 of 98
  • Hardware and Architecture 240
  • Structural Biology 50
  • Media Technology 306
  • Computational Mathematics 12
  • Computational Theory and Mathematics 214
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Francisco D. Igual Spain
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Citations per field
00.5×10×16.7×
Francisco D. Igual · 1×
Citations per year

Countries citing papers authored by Ester M. Garzón

Since Specialization
Citations

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

Fields of papers citing papers by Ester M. Garzón

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ester M. Garzón. 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 Ester M. Garzón. The network helps show where Ester M. Garzón may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 79 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013277
2 201091
3 201087
4 201132
5 201228
6 202026
7 201024
8
The sparse matrix vector product on GPUs
201124
9 201423
10 201322
11 201619
12 200918
13 202118
14 201117
15 201017
16 201113
17 201412
18 200612
19 201811
20 201111

About Ester M. Garzón

Ester M. Garzón is a scholar working on Computational Theory and Mathematics, Artificial Intelligence, Computer Networks and Communications, Hardware and Architecture and Electrical and Electronic Engineering, having authored 79 papers that have together received 1000 indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (15 papers), Quantum Information and Cryptography (11 papers), Matrix Theory and Algorithms (11 papers), Parallel Computing and Optimization Techniques (11 papers), Quantum-Dot Cellular Automata (10 papers), Distributed and Parallel Computing Systems (7 papers), Graph Theory and Algorithms (6 papers) and Advanced Electron Microscopy Techniques and Applications (6 papers). The work is most often cited by research in Hardware and Architecture (240 citations), Structural Biology (50 citations), Media Technology (306 citations), Computational Mathematics (12 citations) and Computational Theory and Mathematics (214 citations). Ester M. Garzón has collaborated with scholars based in Spain, Lithuania and Germany. Frequent co-authors include I. García, José‐Jesús Fernández, Antonio Plaza, Gloria Ortega, José A. Martínez, Ernestas Filatovas, Francisco Javier Las Heras‐Vázquez, Antonio M. Puertas, Siham Tabik and Elías F. Combarro. Their work appears in journals such as The Journal of Supercomputing, Journal of Global Optimization, Journal of Structural Biology, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing and The Computer 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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