Anupam Khatua

641 citations
17 papers · 456 indexed · h-index 10
Topics
COVID-19 epidemiological studies (13 papers)Mathematical and Theoretical Epidemiology and Ecology Models (13 papers)Evolution and Genetic Dynamics (6 papers)
Partner nations
IndiaRussiaGermany

In The Last Decade

Anupam Khatua

16 papers receiving 439 citations

Peers

Anupam Khatua
Comparison fields: 5 of 77
  • Modeling and Simulation 367
  • Public Health, Environmental and Occupational Health 232
  • Infectious Diseases 114
  • Economics and Econometrics 84
  • Genetics 66
Replace Manotosh Mandal with:
Manotosh Mandal India
Swapan Kumar Nandi India
Attila Dénes Hungary
Md. Kamrujjaman Bangladesh
Jayanta Mondal India
Faïçal Ndaïrou Portugal
Kankan Sarkar India
Syafruddin Side Indonesia
Suwardi Annas Indonesia
Sayani Adak India
Anupam Khatua relative to Manotosh Mandal India Manotosh Mandal's profile →
Citations per field
00.5×1.5×
Manotosh Mandal · 1×
Citations per year

Countries citing papers authored by Anupam Khatua

Since Specialization
Citations

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

Fields of papers citing papers by Anupam Khatua

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anupam Khatua

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

All Works

17 of 17 papers shown
#WorkIndexed citations
1 7
2 2
3 1
4 24
5 4
6 1
7 4
8 0
9 22
10 11
11 16
12 18
13 289
14 11
15 11
16 23
17 12

About Anupam Khatua

Anupam Khatua is a scholar working on Modeling and Simulation, Public Health, Environmental and Occupational Health and Genetics, having authored 17 papers that have together received 456 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (13 papers), Mathematical and Theoretical Epidemiology and Ecology Models (13 papers) and Evolution and Genetic Dynamics (6 papers). The work is most often cited by research in Modeling and Simulation (367 citations), Public Health, Environmental and Occupational Health (232 citations) and Infectious Diseases (114 citations). Anupam Khatua has collaborated with scholars based in India, Russia and Germany. Frequent co-authors include T. K. Kar, Soovoojeet Jana, Manotosh Mandal, Swapan Kumar Nandi, Sayani Adak, Dhiraj Kumar Das and Yun Kang. Their work appears in journals such as Chaos Solitons & Fractals, Applied Mathematics and Computation and Chaos An Interdisciplinary Journal of Nonlinear Science.

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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