Luis M. Vaquero

6.8k citations
55 papers · 4.1k indexed · 3 hit papers · h-index 22
Topics
Cloud Computing and Resource Management (15 papers)Cardiac electrophysiology and arrhythmias (13 papers)Distributed and Parallel Computing Systems (9 papers)

In The Last Decade

Luis M. Vaquero

52 papers receiving 3.7k citations

Hit Papers

A break in the clouds200820262014202020082014201150010001.5k

Peers

Luis M. Vaquero
Comparison fields: 5 of 147
  • Information Systems 2.4k
  • Computer Networks and Communications 2.4k
  • Artificial Intelligence 528
  • Cardiology and Cardiovascular Medicine 485
  • Electrical and Electronic Engineering 307
Replace Wei Tan with:
Wei Tan United States
Lizhen Cui China
Attila Kertész Hungary
Antony Tang Australia
Yun Yang Australia
Giuliano Antoniol Canada
Nan Niu United States
Chen Wang China
David M. Weiss United States
Marjan Gušev North Macedonia
Luis M. Vaquero relative to Wei Tan United States Wei Tan's profile →
Citations per field
00.5×10×20×26.9×
Wei Tan · 1×
Citations per year

Countries citing papers authored by Luis M. Vaquero

Since Specialization
Citations

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

Fields of papers citing papers by Luis M. Vaquero

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Luis M. Vaquero

This figure shows the co-authorship network connecting the top 25 collaborators of Luis M. Vaquero. A scholar is included among the top collaborators of Luis M. Vaquero 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 Luis M. Vaquero. Luis M. Vaquero is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 58
3 6
4 12
5
Finding your Way in the Fogbreakdown →
753
6 53
7 2
8 90
9 13
10
Dynamically scaling applications in the cloudbreakdown →
251
11 49
12 127
13 40
14 19
15 45
16 0
17 26
18 69
19 27
20 12

About Luis M. Vaquero

Luis M. Vaquero is a scholar working on Computer Networks and Communications, Information Systems and Cardiology and Cardiovascular Medicine, having authored 55 papers that have together received 4.1k indexed citations. Recurring topics across this work include Cloud Computing and Resource Management (15 papers), Cardiac electrophysiology and arrhythmias (13 papers) and Distributed and Parallel Computing Systems (9 papers). The work is most often cited by research in Information Systems (2.4k citations), Computer Networks and Communications (2.4k citations) and Information Systems and Management (251 citations). Luis M. Vaquero has collaborated with scholars based in Spain, United Kingdom and United States. Frequent co-authors include Luis Rodero‐Merino, Juan Cáceres, Maik Lindner, Rajkumar Buyya, Daniel Morán, José Jalife, David Calvo, Ricardo Caballero, Juan Tamargo and Ricardo Gómez. Their work appears in journals such as Circulation Research, Scientific Reports and Annals of the New York Academy of Sciences.

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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