Laxmisha Rai

897 citations
49 papers · 580 indexed · h-index 12
Topics
Traffic control and management (6 papers)Traffic Prediction and Management Techniques (6 papers)Online Learning and Analytics (5 papers)

In The Last Decade

Laxmisha Rai

42 papers receiving 546 citations

Peers

Laxmisha Rai
Comparison fields: 5 of 104
  • Sociology and Political Science 91
  • Computer Science Applications 89
  • Control and Systems Engineering 81
  • Clinical Psychology 73
  • Artificial Intelligence 68
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Murray Sinclair United Kingdom
Géraldine Heilporn Canada
Scott Davidoff United States
Annapaola Marconi Italy
Flavius Kehr Switzerland
Richard Hauxwell‐Baldwin United Kingdom
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Himanshu Verma Netherlands
James Colley United Kingdom
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Citations per field
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Citations per year

Countries citing papers authored by Laxmisha Rai

Since Specialization
Citations

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

Fields of papers citing papers by Laxmisha Rai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Laxmisha Rai

This figure shows the co-authorship network connecting the top 25 collaborators of Laxmisha Rai. A scholar is included among the top collaborators of Laxmisha Rai 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 Laxmisha Rai. Laxmisha Rai 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 1
2 8
3 7
4 1
5
Unidirectional Flow: A Survey on Networks,Applications, and Characteristic Attributes
0
6 0
7 41
8 14
9 68
10 12
11 5
12 4
13 1
14 84
15 0
16 1
17 0
18
Intelligent gesture generation in Humanoid robot using multi-component synchronization and coordination
8
19 4
20
Embedded Real-Time Software Architecture for Unmanned Autonomous Helicopters
3

About Laxmisha Rai

Laxmisha Rai is a scholar working on Computer Science Applications, Transportation and Computer Vision and Pattern Recognition, having authored 49 papers that have together received 580 indexed citations. Recurring topics across this work include Traffic control and management (6 papers), Traffic Prediction and Management Techniques (6 papers) and Online Learning and Analytics (5 papers). The work is most often cited by research in Computer Science Applications (89 citations), Information Systems and Management (44 citations) and Public Administration (21 citations). Laxmisha Rai has collaborated with scholars based in China, South Korea and Hong Kong. Frequent co-authors include Xin Li, Liu Fan, Haiqing Liu, Zhang Xiao-ping, Yuan‐Wei Du, Xiaoping Zhang, Soon Ju Kang, Haiqing Liu, Jianchun Wang and Na Li. Their work appears in journals such as PLoS ONE, IEEE Access and Sensors.

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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