K. M. Ariful Kabir

2.2k citations
74 papers · 1.7k indexed · h-index 24
Topics
COVID-19 epidemiological studies (41 papers)Mathematical and Theoretical Epidemiology and Ecology Models (27 papers)Evolutionary Game Theory and Cooperation (26 papers)
Partner nations
BangladeshJapanIndia

In The Last Decade

K. M. Ariful Kabir

69 papers receiving 1.7k citations

Peers

K. M. Ariful Kabir
Comparison fields: 5 of 113
  • Modeling and Simulation 898
  • Public Health, Environmental and Occupational Health 654
  • Sociology and Political Science 591
  • Statistical and Nonlinear Physics 420
  • Genetics 315
Replace Piero Manfredi with:
Piero Manfredi Italy
Kazuki Kuga Japan
Michele Tizzoni Italy
Håkan Andersson Sweden
Laurent Hébert‐Dufresne United States
Piero Poletti Italy
Philip C. Cooley United States
Paolo Bajardi Italy
Eunha Shim South Korea
Michelle Kendall United Kingdom
K. M. Ariful Kabir relative to Piero Manfredi Italy Piero Manfredi's profile →
Citations per field
00.5×1.5×2.3×
Piero Manfredi · 1×
Citations per year

Countries citing papers authored by K. M. Ariful Kabir

Since Specialization
Citations

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

Fields of papers citing papers by K. M. Ariful Kabir

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by K. M. Ariful Kabir. 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 K. M. Ariful Kabir. The network helps show where K. M. Ariful Kabir may publish in the future.

Co-authorship network of co-authors of K. M. Ariful Kabir

This figure shows the co-authorship network connecting the top 25 collaborators of K. M. Ariful Kabir. A scholar is included among the top collaborators of K. M. Ariful Kabir 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 K. M. Ariful Kabir. K. M. Ariful Kabir 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 0
2 2
3 0
4 2
5 0
6 0
7 2
8 2
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11 8
12 8
13 7
14 10
15 24
16 31
17 22
18 17
19 37
20 2

About K. M. Ariful Kabir

K. M. Ariful Kabir is a scholar working on Modeling and Simulation, Public Health, Environmental and Occupational Health and Safety Research, having authored 74 papers that have together received 1.7k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (41 papers), Mathematical and Theoretical Epidemiology and Ecology Models (27 papers) and Evolutionary Game Theory and Cooperation (26 papers). The work is most often cited by research in Modeling and Simulation (898 citations), Statistical and Nonlinear Physics (420 citations) and Public Health, Environmental and Occupational Health (654 citations). K. M. Ariful Kabir has collaborated with scholars based in Bangladesh, Japan and India. Frequent co-authors include Jun Tanimoto, Kazuki Kuga, Md. Rajib Arefin, Marko Jusup, Zhen Wang, Bidyut Baran Saha, Hiromu Ito, M. Higazy, Masaki Tanaka and Khurshid Alam. Their work appears in journals such as PLoS ONE, Scientific Reports and Journal of Theoretical Biology.

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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