Sushil Chandra

897 citations
57 papers · 566 · h-index 14

Impact in

Papers in

    • EEG and Brain-Computer Interfaces 19
    • Neural and Behavioral Psychology Studies 6
    • Functional Brain Connectivity Studies 5
    • Neural dynamics and brain function 5
    • Cognitive Science and Mapping 5

Sushil Chandra

52 papers receiving 544 citations

Peers

Sushil Chandra
Comparison fields: 5 of 123
  • Human-Computer Interaction 116
  • Cognitive Neuroscience 195
  • Experimental and Cognitive Psychology 63
  • Automotive Engineering 49
  • Social Psychology 70
Replace Daniel Gromer with:
Daniel Gromer Germany
Karl F. Van Orden United States
Andrea H. Mason United States
Farid I. Kandil Germany
Larry C. Walrath United States
Trevor J. Hine Australia
Angelica M. Tinga Netherlands
Chad C. Williams Canada
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Citations per field
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Citations per year

Countries citing papers authored by Sushil Chandra

Since Specialization
Citations

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

Fields of papers citing papers by Sushil Chandra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199473
2 201963
3 201743
4 201735
5 201535
6 201533
7 201626
8 201522
9 201821
10 201621
11 202421
12 202017
13 201514
14 201713
15 201711
16 202410
17 20018
18 20158
19 20227
20 20236

About Sushil Chandra

Sushil Chandra is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Social Psychology, Clinical Psychology and Automotive Engineering, having authored 57 papers that have together received 566 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (19 papers), Neural and Behavioral Psychology Studies (6 papers), Human-Automation Interaction and Safety (6 papers), Spatial Cognition and Navigation (6 papers), Mindfulness and Compassion Interventions (5 papers), Cognitive Science and Mapping (5 papers), Functional Brain Connectivity Studies (5 papers) and Neural dynamics and brain function (5 papers). The work is most often cited by research in Human-Computer Interaction (116 citations), Cognitive Neuroscience (195 citations), Experimental and Cognitive Psychology (63 citations), Automotive Engineering (49 citations) and Social Psychology (70 citations). Sushil Chandra has collaborated with scholars based in India, Germany and United States. Frequent co-authors include Philip S. Low, Alok Prakash Mittal, Shruti Singh, Priyanka Srivastava, Pawan Kumar Gautam, Vijander Singh, Varun Dutt, Ashok K. Dubey, S. Bhargava and Manjeet Singh Bhatia. Their work appears in journals such as Brain Informatics, Frontiers in Psychology, Big Data, Brain Connectivity and Applied Biochemistry and Biotechnology.

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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