Norman C. Severo

55 total papers · 709 total citations
38 papers, 505 citations indexed

About

Norman C. Severo is a scholar working on Mathematical Physics, Public Health, Environmental and Occupational Health and Modeling and Simulation. According to data from OpenAlex, Norman C. Severo has authored 38 papers receiving a total of 505 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Mathematical Physics, 11 papers in Public Health, Environmental and Occupational Health and 11 papers in Modeling and Simulation. Recurrent topics in Norman C. Severo's work include Mathematical and Theoretical Epidemiology and Ecology Models (11 papers), COVID-19 epidemiological studies (9 papers) and Stochastic processes and statistical mechanics (8 papers). Norman C. Severo is often cited by papers focused on Mathematical and Theoretical Epidemiology and Ecology Models (11 papers), COVID-19 epidemiological studies (9 papers) and Stochastic processes and statistical mechanics (8 papers). Norman C. Severo collaborates with scholars based in United States, Egypt and Taiwan. Norman C. Severo's co-authors include Marvin Zelen, Richard J. Kryscio, Edwin G. Olds, Bernard Levin, Lynne Billard, W. J. Youden and W. S. Connor and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Statistical Association and Technometrics.

In The Last Decade

Norman C. Severo

34 papers receiving 446 citations

Author Peers

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

Author						Papers	Cites
Norman C. Severo	188	188	107	83	81	38	505
Patricia Román‐Román	93 0.5×	213 1.1×	56 0.5×	24 0.3×	95 1.2×	50	604
Adam Bobrowski	29 0.2×	118 0.6×	246 2.3×	78 0.9×	56 0.7×	72	608
Jinghai Shao	100 0.5×	159 0.8×	93 0.9×	65 0.8×	52 0.6×	49	481
Bing Li	55 0.3×	36 0.2×	97 0.9×	32 0.4×	38 0.5×	49	515
P Tautu	45 0.2×	35 0.2×	43 0.4×	93 1.1×	37 0.5×	21	476
Thierry Huillet	34 0.2×	27 0.1×	188 1.8×	59 0.7×	86 1.1×	110	454
Alexandra Smirnova	70 0.4×	190 1.0×	219 2.0×	16 0.2×	17 0.2×	47	549
Thomas Lorenz	43 0.2×	113 0.6×	71 0.7×	12 0.1×	54 0.7×	52	561
Qian Guo	48 0.3×	309 1.6×	15 0.1×	60 0.7×	26 0.3×	50	607
Florent Malrieu	25 0.1×	77 0.4×	201 1.9×	57 0.7×	186 2.3×	22	613

Countries citing papers authored by Norman C. Severo

Since Specialization

Citations

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

Fields of papers citing papers by Norman C. Severo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Norman C. Severo. 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 Norman C. Severo. The network helps show where Norman C. Severo may publish in the future.

Co-authorship network of co-authors of Norman C. Severo

This figure shows the co-authorship network connecting the top 25 collaborators of Norman C. Severo. A scholar is included among the top collaborators of Norman C. Severo 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 Norman C. Severo. Norman C. Severo 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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