Anil K. Ghosh

3.2k citations
81 papers · 2.1k indexed · h-index 24
Topics
Statistical Methods and Inference (31 papers)Advanced Statistical Methods and Models (16 papers)Bayesian Methods and Mixture Models (11 papers)

In The Last Decade

Anil K. Ghosh

80 papers receiving 2.0k citations

Peers

Anil K. Ghosh
Comparison fields: 5 of 188
  • Molecular Biology 560
  • Public Health, Environmental and Occupational Health 506
  • Statistics and Probability 432
  • Immunology 386
  • Artificial Intelligence 353
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Citations per field
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Citations per year

Countries citing papers authored by Anil K. Ghosh

Since Specialization
Citations

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

Fields of papers citing papers by Anil K. Ghosh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Anil K. Ghosh. 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 Anil K. Ghosh. The network helps show where Anil K. Ghosh may publish in the future.

Co-authorship network of co-authors of Anil K. Ghosh

This figure shows the co-authorship network connecting the top 25 collaborators of Anil K. Ghosh. A scholar is included among the top collaborators of Anil K. Ghosh 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 Anil K. Ghosh. Anil K. Ghosh 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 5
2 1
3 1
4 7
5 9
6 3
7 18
8 4
9 37
10 23
11 64
12
Applied MANOVA and Discriminant Analysis (2nd ed.). Carl J. Huberty and Stephen Olejnik
8
13
Comparative study of ppen mesh repair and Desarda’s no-mesh repair in a District Hospital in India
12
14 48
15 30
16
Some geochemical characteristics of the lead-dominant sulphide mineralisation at Sargipali, Sundergarh District, Orissa
1
17
Mineral wealth of the Ocean: A treatise on distribution, origin, exploration, mining and management of sea floor non-living resources
4
18 1
19
Internal constitution of manganese nodules from the central Indian Ocean Basin
4
20
Distribution, Morphology, and Geochemistry of Manganese Nodules from the Valivia 13/2 Area, Equatorial North Pacific
10

About Anil K. Ghosh

Anil K. Ghosh is a scholar working on Statistics and Probability, Geochemistry and Petrology and Artificial Intelligence, having authored 81 papers that have together received 2.1k indexed citations. Recurring topics across this work include Statistical Methods and Inference (31 papers), Advanced Statistical Methods and Models (16 papers) and Bayesian Methods and Mixture Models (11 papers). The work is most often cited by research in Statistics and Probability (432 citations), Insect Science (323 citations) and Immunology (386 citations). Anil K. Ghosh has collaborated with scholars based in India, United States and United Kingdom. Frequent co-authors include Marcelo Jacobs‐Lorena, Luciano Andrade Moreira, Probal Chaudhuri, Junitsu Ito, Ernst A. Wimmer, Munmun Biswas, Soham Sarkar, Ranadhir Mukhopadhyay, Eappen G. Abraham and C.A. Murthy. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

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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