Joon Sik Kim

90 total papers · 1.4k total citations
44 papers, 836 citations indexed

About

Joon Sik Kim is a scholar working on Pulmonary and Respiratory Medicine, Pediatrics, Perinatology and Child Health and Epidemiology. According to data from OpenAlex, Joon Sik Kim has authored 44 papers receiving a total of 836 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Pulmonary and Respiratory Medicine, 6 papers in Pediatrics, Perinatology and Child Health and 6 papers in Epidemiology. Recurrent topics in Joon Sik Kim's work include Smart Cities and Technologies (3 papers), Adversarial Robustness in Machine Learning (3 papers) and Explainable Artificial Intelligence (XAI) (3 papers). Joon Sik Kim is often cited by papers focused on Smart Cities and Technologies (3 papers), Adversarial Robustness in Machine Learning (3 papers) and Explainable Artificial Intelligence (XAI) (3 papers). Joon Sik Kim collaborates with scholars based in South Korea, China and United States. Joon Sik Kim's co-authors include Ameet Talwalkar, Gregory Plumb, Valerie Chen, Jeffrey Li, Jinglu Song, Bo Huang, Jiahong Wen, Rongrong Li, Peter W. J. Batey and Chih‐Kuan Yeh and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Science of The Total Environment and Communications of the ACM.

In The Last Decade

Joon Sik Kim

39 papers receiving 801 citations

Hit Papers

Interpretable Machine Lea... 2021 2026 2022 2024 2021 2022 100 200 300

Author Peers

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

Author Last Decade Papers Cites
Joon Sik Kim 253 74 71 65 58 44 836
Trang T. Le 156 0.6× 63 0.9× 20 0.3× 51 0.8× 36 0.6× 36 830
Yasunobu Nohara 150 0.6× 27 0.4× 29 0.4× 76 1.2× 115 2.0× 55 910
Angela Lombardi 221 0.9× 51 0.7× 36 0.5× 40 0.6× 10 0.2× 48 752
Aris Perperoglou 99 0.4× 30 0.4× 27 0.4× 26 0.4× 46 0.8× 37 908
Gonzalo Acuña 117 0.5× 62 0.8× 63 0.9× 79 1.2× 69 1.2× 33 844
Philipp Probst 177 0.7× 17 0.2× 50 0.7× 12 0.2× 85 1.5× 17 863
Valeria Vitelli 254 1.0× 9 0.1× 51 0.7× 45 0.7× 47 0.8× 46 894
Sounak Chakraborty 319 1.3× 17 0.2× 25 0.4× 17 0.3× 74 1.3× 33 887
Steven J. Rigatti 169 0.7× 23 0.3× 57 0.8× 13 0.2× 61 1.1× 12 939
Michael G. Schimek 68 0.3× 102 1.4× 57 0.8× 53 0.8× 22 0.4× 38 759

Countries citing papers authored by Joon Sik Kim

Since Specialization
Citations

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

Fields of papers citing papers by Joon Sik Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joon Sik Kim

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