Seonjin Kim

47 total papers · 791 total citations
27 papers, 419 citations indexed

About

Seonjin Kim is a scholar working on Statistics and Probability, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, Seonjin Kim has authored 27 papers receiving a total of 419 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Statistics and Probability, 8 papers in Artificial Intelligence and 3 papers in Molecular Biology. Recurrent topics in Seonjin Kim's work include Statistical Methods and Inference (15 papers), Statistical Methods and Bayesian Inference (9 papers) and Bayesian Methods and Mixture Models (5 papers). Seonjin Kim is often cited by papers focused on Statistical Methods and Inference (15 papers), Statistical Methods and Bayesian Inference (9 papers) and Bayesian Methods and Mixture Models (5 papers). Seonjin Kim collaborates with scholars based in United States, South Korea and China. Seonjin Kim's co-authors include Zhibiao Zhao, Jane E. Clark, Nádia Cristina Valentini, Yuwei Xie, John P. Giesy, Jianghua Yang, Hongxia Yu, Jong Seong Khim, Seongjin Hong and Xiaowei Zhang and has published in prestigious journals such as Biometrics, Environmental Pollution and Chemosphere.

In The Last Decade

Seonjin Kim

23 papers receiving 408 citations

Author Peers

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

Author						Papers	Cites
Seonjin Kim	222	71	51	47	43	27	419
Myriam Maumy‐Bertrand	101 0.5×	80 1.1×	12 0.2×	25 0.5×	19 0.4×	38	480
Daniel Lee	45 0.2×	34 0.5×	15 0.3×	62 1.3×	50 1.2×	12	428
Janis E. Johnston	33 0.1×	45 0.6×	22 0.4×	108 2.3×	43 1.0×	46	411
Mariangela Sciandra	17 0.1×	101 1.4×	8 0.2×	35 0.7×	34 0.8×	33	399
Jun Chen	211 1.0×	58 0.8×	12 0.2×	16 0.3×	19 0.4×	22	440
Viviana Giampaoli	38 0.2×	22 0.3×	6 0.1×	44 0.9×	15 0.3×	28	456
Shanshan Shao	59 0.3×	10 0.1×	155 3.0×	56 1.2×	5 0.1×	25	457
Zhe Fei	172 0.8×	84 1.2×	5 0.1×	21 0.4×	44 1.0×	39	477
Hervé Perdry	85 0.4×	6 0.1×	38 0.7×	36 0.8×	12 0.3×	48	439
Carol J. Feltz	27 0.1×	28 0.4×	47 0.9×	136 2.9×	64 1.5×	17	432

Countries citing papers authored by Seonjin Kim

Since Specialization

Citations

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

Fields of papers citing papers by Seonjin Kim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Seonjin Kim

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