Sung-Kyun Kim

30 total papers · 456 total citations
20 papers, 165 citations indexed

About

Sung-Kyun Kim is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Sung-Kyun Kim has authored 20 papers receiving a total of 165 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 7 papers in Artificial Intelligence and 6 papers in Control and Systems Engineering. Recurrent topics in Sung-Kyun Kim's work include Robotic Path Planning Algorithms (5 papers), Reinforcement Learning in Robotics (4 papers) and Robot Manipulation and Learning (4 papers). Sung-Kyun Kim is often cited by papers focused on Robotic Path Planning Algorithms (5 papers), Reinforcement Learning in Robotics (4 papers) and Robot Manipulation and Learning (4 papers). Sung-Kyun Kim collaborates with scholars based in United States, South Korea and Canada. Sung-Kyun Kim's co-authors include Ali‐akbar Agha‐mohammadi, Maxim Likhachev, Kyohei Otsu, Joel W. Burdick, Young-Il Chang, Gautam Salhotra, David D. Fan, Seung‐Hak Baek, Suman Chakravorty and Nancy M. Amato and has published in prestigious journals such as IEEE Transactions on Robotics, IEEE Robotics and Automation Letters and The Angle Orthodontist.

In The Last Decade

Sung-Kyun Kim

20 papers receiving 159 citations

Author Peers

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

Author Last Decade Papers Cites
Sung-Kyun Kim 72 54 43 32 30 20 165
Lorenzo Flückiger 53 0.7× 68 1.3× 77 1.8× 60 1.9× 16 0.5× 16 200
Michael McHenry 59 0.8× 71 1.3× 25 0.6× 32 1.0× 18 0.6× 10 165
David D. Fan 68 0.9× 57 1.1× 31 0.7× 29 0.9× 18 0.6× 17 144
Kimberly Hambuchen 61 0.8× 57 1.1× 105 2.4× 55 1.7× 14 0.5× 18 213
Carlos Agüero 78 1.1× 52 1.0× 75 1.7× 38 1.2× 26 0.9× 18 237
Peter Lehner 61 0.8× 43 0.8× 56 1.3× 19 0.6× 7 0.2× 23 139
Jack Collier 116 1.6× 100 1.9× 113 2.6× 34 1.1× 9 0.3× 23 263
Muhammad Fadhil Ginting 79 1.1× 95 1.8× 24 0.6× 18 0.6× 26 0.9× 11 147
Shashank Govindaraj 60 0.8× 120 2.2× 21 0.5× 19 0.6× 21 0.7× 17 215
Albert J. Wavering 83 1.2× 40 0.7× 72 1.7× 22 0.7× 12 0.4× 20 185

Countries citing papers authored by Sung-Kyun Kim

Since Specialization
Citations

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

Fields of papers citing papers by Sung-Kyun Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sung-Kyun Kim

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