Sunil Kumar Mishra

37 total papers · 569 total citations
20 papers, 303 citations indexed

About

Sunil Kumar Mishra is a scholar working on Artificial Intelligence, Endocrinology, Diabetes and Metabolism and Computer Networks and Communications. According to data from OpenAlex, Sunil Kumar Mishra has authored 20 papers receiving a total of 303 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 3 papers in Endocrinology, Diabetes and Metabolism and 2 papers in Computer Networks and Communications. Recurrent topics in Sunil Kumar Mishra's work include Semantic Web and Ontologies (9 papers), AI-based Problem Solving and Planning (5 papers) and Topic Modeling (4 papers). Sunil Kumar Mishra is often cited by papers focused on Semantic Web and Ontologies (9 papers), AI-based Problem Solving and Planning (5 papers) and Topic Modeling (4 papers). Sunil Kumar Mishra collaborates with scholars based in United States, India and Spain. Sunil Kumar Mishra's co-authors include Vinay K. Chaudhri, Bruce Porter, Ken Barker, Peter E. Clark, Nandita Gupta, Kiran Kumar Ravulakollu, Ravinder Goswami, Andrés Rodríguez, Yolanda Gil and Patrick J. Hayes and has published in prestigious journals such as The Journal of Clinical Endocrinology & Metabolism, Archives of Gerontology and Geriatrics and AI Magazine.

In The Last Decade

Sunil Kumar Mishra

19 papers receiving 259 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Sunil Kumar Mishra 177 38 30 29 28 20 303
Łukasz Juszczyk 57 0.3× 114 3.0× 52 1.7× 52 1.8× 121 4.3× 17 313
Bilal Khan 122 0.7× 83 2.2× 6 0.2× 8 0.3× 38 1.4× 31 338
Huma Naz 170 1.0× 19 0.5× 14 0.5× 34 1.2× 6 0.2× 21 365
Tagne Poupi Theodore Armand 69 0.4× 70 1.8× 35 1.2× 17 0.6× 47 1.7× 24 347
Xuemei Luo 157 0.9× 8 0.2× 17 0.6× 26 0.9× 46 1.6× 21 336
Nelia Lasierra 91 0.5× 49 1.3× 9 0.3× 54 1.9× 29 1.0× 20 241
Nikos Fazakis 189 1.1× 33 0.9× 2 0.1× 9 0.3× 18 0.6× 25 310
Ludwik Finkelstein 29 0.2× 12 0.3× 15 0.5× 23 0.8× 32 1.1× 15 281
Karthik Sekaran 63 0.4× 122 3.2× 11 0.4× 37 1.3× 121 4.3× 32 303
Cynthia R. Marling 80 0.5× 22 0.6× 14 0.5× 14 0.5× 12 0.4× 20 358

Countries citing papers authored by Sunil Kumar Mishra

Since Specialization
Citations

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

Fields of papers citing papers by Sunil Kumar Mishra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sunil Kumar Mishra. 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 Sunil Kumar Mishra. The network helps show where Sunil Kumar Mishra may publish in the future.

Co-authorship network of co-authors of Sunil Kumar Mishra

This figure shows the co-authorship network connecting the top 25 collaborators of Sunil Kumar Mishra. A scholar is included among the top collaborators of Sunil Kumar Mishra 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 Sunil Kumar Mishra. Sunil Kumar Mishra is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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