Youngeun Kwon

16 total papers · 487 total citations
8 papers, 306 citations indexed

About

Youngeun Kwon is a scholar working on Hardware and Architecture, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Youngeun Kwon has authored 8 papers receiving a total of 306 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Hardware and Architecture, 5 papers in Electrical and Electronic Engineering and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Youngeun Kwon's work include Parallel Computing and Optimization Techniques (5 papers), Ferroelectric and Negative Capacitance Devices (4 papers) and Advanced Neural Network Applications (3 papers). Youngeun Kwon is often cited by papers focused on Parallel Computing and Optimization Techniques (5 papers), Ferroelectric and Negative Capacitance Devices (4 papers) and Advanced Neural Network Applications (3 papers). Youngeun Kwon collaborates with scholars based in South Korea and Canada. Youngeun Kwon's co-authors include Minsoo Rhu, Y. Lee and John Kim and has published in prestigious journals such as IEEE Micro and IEEE Computer Architecture Letters.

In The Last Decade

Youngeun Kwon

8 papers receiving 293 citations

Author Peers

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

Author						Papers	Cites
Youngeun Kwon	130	118	114	99	95	8	306
Xinfeng Xie	119 0.9×	119 1.0×	110 1.0×	38 0.4×	154 1.6×	15	299
Denis Foley	197 1.5×	60 0.5×	105 0.9×	55 0.6×	224 2.4×	9	357
Jinhong Zhou	80 0.6×	112 0.9×	153 1.3×	39 0.4×	109 1.1×	17	339
Hyunsung Shin	140 1.1×	38 0.3×	182 1.6×	33 0.3×	169 1.8×	6	315
Chien-Chin Huang	52 0.4×	84 0.7×	55 0.5×	19 0.2×	57 0.6×	8	217
Jacques A. Pienaar	142 1.1×	107 0.9×	58 0.5×	56 0.6×	234 2.5×	8	358
Lingxiao Ma	68 0.5×	242 2.1×	56 0.5×	50 0.5×	71 0.7×	16	344
Mark Gottscho	142 1.1×	64 0.5×	206 1.8×	39 0.4×	188 2.0×	19	360
Joonho Song	87 0.7×	61 0.5×	179 1.6×	19 0.2×	102 1.1×	16	302
Newsha Ardalani	173 1.3×	53 0.4×	79 0.7×	46 0.5×	212 2.2×	13	315

Countries citing papers authored by Youngeun Kwon

Since Specialization

Citations

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

Fields of papers citing papers by Youngeun Kwon

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Youngeun Kwon

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