M. Pitchaimani

73 total papers · 680 total citations
56 papers, 509 citations indexed

About

M. Pitchaimani is a scholar working on Public Health, Environmental and Occupational Health, Modeling and Simulation and Genetics. According to data from OpenAlex, M. Pitchaimani has authored 56 papers receiving a total of 509 indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Public Health, Environmental and Occupational Health, 26 papers in Modeling and Simulation and 22 papers in Genetics. Recurrent topics in M. Pitchaimani's work include Mathematical and Theoretical Epidemiology and Ecology Models (36 papers), Evolution and Genetic Dynamics (22 papers) and COVID-19 epidemiological studies (11 papers). M. Pitchaimani is often cited by papers focused on Mathematical and Theoretical Epidemiology and Ecology Models (36 papers), Evolution and Genetic Dynamics (22 papers) and COVID-19 epidemiological studies (11 papers). M. Pitchaimani collaborates with scholars based in India, China and United States. M. Pitchaimani's co-authors include Quanxin Zhu, Tarynn M. Witten, B. S. Chandrasekhar, Vineet K. Srivastava, Ashutosh Ashutosh, Kaibo Shi, Keerthana Krishnan, Noura Yousfi and Konda Mani Saravanan and has published in prestigious journals such as SHILAP Revista de lepidopterología, Gene and Physica A Statistical Mechanics and its Applications.

In The Last Decade

M. Pitchaimani

50 papers receiving 485 citations

Author Peers

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

Author						Papers	Cites
M. Pitchaimani	357	291	190	41	38	56	509
Wei Hong Yang	251 0.7×	283 1.0×	125 0.7×	22 0.5×	20 0.5×	40	535
Changguo Li	403 1.1×	194 0.7×	226 1.2×	47 1.1×	35 0.9×	51	579
Dashun Xu	334 0.9×	209 0.7×	188 1.0×	41 1.0×	9 0.2×	27	529
János Karsai	361 1.0×	344 1.2×	205 1.1×	48 1.2×	10 0.3×	23	590
Tsuyoshi Kajiwara	311 0.9×	163 0.6×	208 1.1×	45 1.1×	70 1.8×	38	567
Hebatallah J. Alsakaji	400 1.1×	390 1.3×	162 0.9×	42 1.0×	11 0.3×	17	534
Juan Liu	286 0.8×	75 0.3×	79 0.4×	14 0.3×	8 0.2×	66	559
Yali Yang	423 1.2×	349 1.2×	248 1.3×	15 0.4×	14 0.4×	24	500
Xiao‐Bing Zhang	436 1.2×	318 1.1×	218 1.1×	45 1.1×	27 0.7×	33	528
Mohd Hafiz Mohd	383 1.1×	340 1.2×	199 1.0×	37 0.9×	18 0.5×	48	592

Countries citing papers authored by M. Pitchaimani

Since Specialization

Citations

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

Fields of papers citing papers by M. Pitchaimani

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. Pitchaimani

This figure shows the co-authorship network connecting the top 25 collaborators of M. Pitchaimani. A scholar is included among the top collaborators of M. Pitchaimani 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 M. Pitchaimani. M. Pitchaimani 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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