Shangbing Ai

42 total papers · 753 total citations
33 papers, 551 citations indexed

About

Shangbing Ai is a scholar working on Public Health, Environmental and Occupational Health, Modeling and Simulation and Genetics. According to data from OpenAlex, Shangbing Ai has authored 33 papers receiving a total of 551 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Public Health, Environmental and Occupational Health, 12 papers in Modeling and Simulation and 9 papers in Genetics. Recurrent topics in Shangbing Ai's work include Mathematical and Theoretical Epidemiology and Ecology Models (14 papers), Mathematical Biology Tumor Growth (10 papers) and Nonlinear Dynamics and Pattern Formation (8 papers). Shangbing Ai is often cited by papers focused on Mathematical and Theoretical Epidemiology and Ecology Models (14 papers), Mathematical Biology Tumor Growth (10 papers) and Nonlinear Dynamics and Pattern Formation (8 papers). Shangbing Ai collaborates with scholars based in United States, China and Canada. Shangbing Ai's co-authors include Jia Li, Liming Cai, Wenzhang Huang, S. P. Hastings, Jia Li, Yihong Du, Rui Peng, Liming Cai, Guihong Fan and John A. Pelesko and has published in prestigious journals such as Journal of Mathematical Analysis and Applications, Physica D Nonlinear Phenomena and Transactions of the American Mathematical Society.

In The Last Decade

Shangbing Ai

32 papers receiving 517 citations

Author Peers

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

Author						Papers	Cites
Shangbing Ai	375	173	160	147	82	33	551
Jimmy Garnier	235 0.6×	24 0.1×	222 1.4×	122 0.8×	32 0.4×	35	529
Alfonso Ruiz-Herrera	297 0.8×	15 0.1×	166 1.0×	61 0.4×	91 1.1×	54	495
Nicolas Vauchelet	188 0.5×	104 0.6×	52 0.3×	295 2.0×	19 0.2×	64	576
Yuanshun Tan	157 0.4×	23 0.1×	79 0.5×	91 0.6×	173 2.1×	38	501
Yunfei Lv	424 1.1×	13 0.1×	240 1.5×	153 1.0×	148 1.8×	42	515
Yannick Privat	113 0.3×	77 0.4×	37 0.2×	38 0.3×	16 0.2×	69	592
Changguo Li	403 1.1×	13 0.1×	226 1.4×	194 1.3×	118 1.4×	51	579
Roslyn I. Hickson	254 0.7×	124 0.7×	44 0.3×	98 0.7×	12 0.1×	42	555
Francesco M. Scudo	127 0.3×	15 0.1×	206 1.3×	65 0.4×	22 0.3×	22	465
Alakes Maiti	469 1.3×	16 0.1×	342 2.1×	183 1.2×	68 0.8×	30	522

Countries citing papers authored by Shangbing Ai

Since Specialization

Citations

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

Fields of papers citing papers by Shangbing Ai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shangbing Ai

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