Divya Chander

657 citations
5 papers · 488 · h-index 5

Impact in

    • Artificial Intelligence in Healthcare and Education
    • Neural dynamics and brain function
    • Visual perception and processing mechanisms
    • EEG and Brain-Computer Interfaces

Papers in

Divya Chander

5 papers receiving 476 citations

Peers

Divya Chander
Comparison fields: 5 of 74
  • Health Informatics 53
  • Cognitive Neuroscience 231
  • Cellular and Molecular Neuroscience 179
  • Anesthesiology and Pain Medicine 45
  • Critical Care and Intensive Care Medicine 21
Replace Christophe Gardella with:
Christophe Gardella France
Masataka Tanaka Japan
W. D. Sheffield United States
Paul Lightfoot Australia
Nishant Sinha United States
Alberto Averna Italy
Alan Chiu United States
Lara Marcuse United States
Joseph G. Makin United States
Divya Chander relative to Christophe Gardella France Christophe Gardella's profile →
Citations per field
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Citations per year

Countries citing papers authored by Divya Chander

Since Specialization
Citations

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

Fields of papers citing papers by Divya Chander

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside Divya Chander, 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 Divya Chander Line = papers co-authored together Divya Chander links everyone, so they are left out of the graph.

All Works

About Divya Chander

Divya Chander is a scholar working on Cognitive Neuroscience, Surgery, Molecular Biology, Cellular and Molecular Neuroscience and Anesthesiology and Pain Medicine, having authored 5 papers that have together received 488 indexed citations. Recurring topics across this work include Neural dynamics and brain function (4 papers), EEG and Brain-Computer Interfaces (2 papers), Artificial Intelligence in Healthcare and Education (1 paper), Neuroscience and Neural Engineering (1 paper), Surgical Simulation and Training (1 paper), Anatomy and Medical Technology (1 paper), Anesthesia and Sedative Agents (1 paper) and Retinal Development and Disorders (1 paper). The work is most often cited by research in Health Informatics (53 citations), Cognitive Neuroscience (231 citations), Cellular and Molecular Neuroscience (179 citations), Anesthesiology and Pain Medicine (45 citations) and Critical Care and Intensive Care Medicine (21 citations). Divya Chander has collaborated with scholars based in United States, New Zealand and Israel. Frequent co-authors include E. J. Chichilnisky, Sandip S. Panesar, Juan C. Fernandez‐Miranda, Jose Morey, Michel Kliot, Yvonne Cagle, Jamie Sleigh, Paul S. García, Rohit Prakash and Thomas J. Richner. Their work appears in journals such as PLoS ONE, IEEE Reviews in Biomedical Engineering, Journal of Neuroscience and Annals of Surgery.

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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