S. Laxminarayan

1.4k citations
54 papers · 944 · h-index 16

Impact in

Papers in

S. Laxminarayan

47 papers receiving 900 citations

Peers

S. Laxminarayan
Comparison fields: 5 of 124
  • Experimental and Cognitive Psychology 255
  • Computer Vision and Pattern Recognition 268
  • Cognitive Neuroscience 199
  • Computational Mathematics 5
  • Endocrine and Autonomic Systems 55
Replace Musa Hakan Asyalı with:
Musa Hakan Asyalı Türkiye
Leonardo Bocchi Italy
Orla Doyle United Kingdom
Kanav Kahol United States
Lakshman S. Tamil United States
Kwang Suk Park South Korea
Do‐Un Jeong South Korea
Walter Karlen Switzerland
Luay Fraiwan Jordan
Oldřich Vyšata Czechia
S. Laxminarayan relative to Musa Hakan Asyalı Türkiye Musa Hakan Asyalı's profile →
Citations per field
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Musa Hakan Asyalı · 1×
Citations per year

Countries citing papers authored by S. Laxminarayan

Since Specialization
Citations

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

Fields of papers citing papers by S. Laxminarayan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 54 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002208
2 2013116
3 200286
4 200244
5 200539
6 201937
7 201936
8 201830
9 201425
10 201524
11 201724
12 202122
13 201221
14 201517
15 201217
16 202017
17 201415
18 200513
19 198413
20 201710

About S. Laxminarayan

S. Laxminarayan is a scholar working on Experimental and Cognitive Psychology, Cognitive Neuroscience, Pulmonary and Respiratory Medicine, Computer Vision and Pattern Recognition and Molecular Biology, having authored 54 papers that have together received 944 indexed citations. Recurring topics across this work include Sleep and Work-Related Fatigue (13 papers), Sleep and related disorders (9 papers), Sleep and Wakefulness Research (9 papers), Thermoregulation and physiological responses (5 papers), EEG and Brain-Computer Interfaces (5 papers), Medical Image Segmentation Techniques (5 papers), Climate Change and Health Impacts (4 papers) and Ergonomics and Musculoskeletal Disorders (3 papers). The work is most often cited by research in Experimental and Cognitive Psychology (255 citations), Computer Vision and Pattern Recognition (268 citations), Cognitive Neuroscience (199 citations), Computational Mathematics (5 citations) and Endocrine and Autonomic Systems (55 citations). S. Laxminarayan has collaborated with scholars based in United States, United Kingdom and Finland. Frequent co-authors include Jaques Reifman, Laura Reden, Kecheng Liu, Jasjit S. Suri, Sridhar Ramakrishnan, Sameer Singh, Xiaolan Zeng, Nancy J. Wesensten, Anne Germain and Srinivasan Rajaraman. Their work appears in journals such as Journal of Sleep Research, SLEEP, Journal of Theoretical Biology, European Journal of Applied Physiology and Journal of science and medicine in sport.

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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