Sven Sigurðsson

1.2k citations
39 papers · 850 indexed · h-index 15
Topics
Numerical methods for differential equations (5 papers)Mathematical and Theoretical Epidemiology and Ecology Models (5 papers)Surfactants and Colloidal Systems (4 papers)
Partner nations
IcelandUgandaDenmark

In The Last Decade

Sven Sigurðsson

38 papers receiving 814 citations

Peers

Sven Sigurðsson
Comparison fields: 5 of 125
  • Cognitive Neuroscience 210
  • Artificial Intelligence 96
  • Atmospheric Science 94
  • Global and Planetary Change 87
  • Signal Processing 78
Replace Joseph D. Skufca with:
Joseph D. Skufca United States
Yan Zhou China
Ying Wu China
Mingjun Wei United States
Yinping Cao China
Chiara Mocenni Italy
Jinshan Xu China
Yoshinori Dobashi Japan
Masahiro Ishii Japan
Malte Siefert Germany
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Citations per field
00.5×3.4×
Joseph D. Skufca · 1×
Citations per year

Countries citing papers authored by Sven Sigurðsson

Since Specialization
Citations

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

Fields of papers citing papers by Sven Sigurðsson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sven Sigurðsson

This figure shows the co-authorship network connecting the top 25 collaborators of Sven Sigurðsson. A scholar is included among the top collaborators of Sven Sigurðsson 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 Sven Sigurðsson. Sven Sigurðsson 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 12
2 4
3 1
4 10
5 31
6 8
7 5
8 14
9 1
10 48
11 1
12 17
13 86
14 50
15 170
16 25
17 106
18 2
19 28
20 1

About Sven Sigurðsson

Sven Sigurðsson is a scholar working on Pharmaceutical Science, Numerical Analysis and Signal Processing, having authored 39 papers that have together received 850 indexed citations. Recurring topics across this work include Numerical methods for differential equations (5 papers), Mathematical and Theoretical Epidemiology and Ecology Models (5 papers) and Surfactants and Colloidal Systems (4 papers). The work is most often cited by research in Cognitive Neuroscience (210 citations), Signal Processing (78 citations) and Pharmaceutical Science (36 citations). Sven Sigurðsson has collaborated with scholars based in Iceland, Uganda and Denmark. Frequent co-authors include Thomas Philip Rúnarsson, Steinn Guðmundsson, Kristinn Johnsen, Kjartan G. Magnússon, Simon J. Hubbard, Leifur Leifsson, J. D. Lambert, Fjóla Jónsdóttir, Kristján Jónasson and Már Másson. Their work appears in journals such as PLoS ONE, Expert Systems with Applications and Journal of Pharmaceutical 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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