Romesh Abeysuriya

3.2k total citations
44 papers, 1.2k citations indexed

About

Romesh Abeysuriya is a scholar working on Modeling and Simulation, Cognitive Neuroscience and Infectious Diseases. According to data from OpenAlex, Romesh Abeysuriya has authored 44 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Modeling and Simulation, 18 papers in Cognitive Neuroscience and 10 papers in Infectious Diseases. Recurrent topics in Romesh Abeysuriya's work include COVID-19 epidemiological studies (19 papers), Neural dynamics and brain function (11 papers) and Functional Brain Connectivity Studies (9 papers). Romesh Abeysuriya is often cited by papers focused on COVID-19 epidemiological studies (19 papers), Neural dynamics and brain function (11 papers) and Functional Brain Connectivity Studies (9 papers). Romesh Abeysuriya collaborates with scholars based in Australia, United States and United Kingdom. Romesh Abeysuriya's co-authors include P. A. Robinson, Mark W. Woolrich, Robert Becker, Andrew J. Quinn, Diego Vidaurre, Chris Rennie, Fidel Alfaro‐Almagro, Stephen M. Smith, Svetlana Postnova and James A. Roberts and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and NeuroImage.

In The Last Decade

Romesh Abeysuriya

39 papers receiving 1.2k citations

Peers

Romesh Abeysuriya
Comparison fields: 5 of 117
  • Cognitive Neuroscience 833
  • Radiology, Nuclear Medicine and Imaging 169
  • Modeling and Simulation 162
  • Experimental and Cognitive Psychology 138
  • Cellular and Molecular Neuroscience 111
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Glenn Lawyer Germany
Shoi Shi Japan
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Maryann D’Alessandro United States
Danny Eytan Israel
Anca Rǎdulescu United States
Uwe an der Heiden Germany
Marianna La Rocca Italy
Rene Markovič Slovenia View profile →
Citations per field, relative to Romesh Abeysuriya
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Citations per year, relative to Romesh Abeysuriya
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Countries citing papers authored by Romesh Abeysuriya

Since Specialization
Citations

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

Fields of papers citing papers by Romesh Abeysuriya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Romesh Abeysuriya

This figure shows the co-authorship network connecting the top 25 collaborators of Romesh Abeysuriya. A scholar is included among the top collaborators of Romesh Abeysuriya 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 Romesh Abeysuriya. Romesh Abeysuriya 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
# Work Indexed citations
1 2
2 3
3 1
4 2
5 6
6 3
7 0
8 6
9 0
10 16
11 22
12
Modelling the impact of reducing control measures on the COVID-19 pandemic in a low transmission setting
2
13 48
14 138
15 65
16 223
17 20
18 34
19 7
20 48

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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