Young D. Kwon

23 papers receiving 338 citations

Peers

Young D. Kwon
Comparison fields: 5 of 81
  • Health Informatics 77
  • Computer Science Applications 77
  • Human-Computer Interaction 24
  • Artificial Intelligence 130
  • Communication 24
Replace Sarang Shaikh with:
Sarang Shaikh Pakistan
Marcin Gruza Poland
Vidya Rajaram United States
Daphne Ippolito United States
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Juho Kahila Finland
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Nayeon Lee South Korea
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Citations per year

Countries citing papers authored by Young D. Kwon

Since Specialization
Citations

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

Fields of papers citing papers by Young D. Kwon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Young D. Kwon, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Young D. Kwon Line = papers co-authored together Young D. Kwon links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2023167
2 202027
3 202022
4 200617
5 202112
6 202210
7 201910
8 202010
9 20199
10 20228
11 20208
12 20207
13 20227
14 20226
15 20236
16 20216
17 20223
18
Statistical Observation on Neonate
19932
19
Clinical Analysis of Postoperative Prognostic Factors of Cervical Anterior Decompression and Interbody Fusion for Ossification of Posterior Longitudinal Ligament.
20002
20 20182

About Young D. Kwon

Young D. Kwon is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics and Electrical and Electronic Engineering, having authored 24 papers that have together received 344 indexed citations. Recurring topics across this work include Social Media and Politics (3 papers), Context-Aware Activity Recognition Systems (3 papers), Complex Network Analysis Techniques (3 papers), Opinion Dynamics and Social Influence (3 papers), User Authentication and Security Systems (2 papers), Interactive and Immersive Displays (2 papers), Advanced Neural Network Applications (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). The work is most often cited by research in Health Informatics (77 citations), Computer Science Applications (77 citations), Human-Computer Interaction (24 citations), Artificial Intelligence (130 citations) and Communication (24 citations). Young D. Kwon has collaborated with scholars based in United Kingdom, Hong Kong and Finland. Frequent co-authors include Pan Hui, Cecilia Mascolo, Jagmohan Chauhan, Reza Hadi Mogavi, Ahmed Hosny Saleh Metwally, Ahmed Tlili, Lennart E. Nacke, Sujit Gujar, Pengyuan Zhou and Chao Deng. Their work appears in journals such as Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, IEEE Transactions on Mobile Computing, Physical Review B, IEEE Access and Journal of Korean Neurosurgical Society.

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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