Hyunkyoo Cho

737 citations
43 papers · 566 indexed · h-index 15

Hyunkyoo Cho

39 papers receiving 560 citations

Peers

Hyunkyoo Cho
Comparison fields: 5 of 45
  • Statistics, Probability and Uncertainty 398
  • Computational Theory and Mathematics 272
  • Management Science and Operations Research 129
  • Civil and Structural Engineering 193
  • Mechanics of Materials 117
Replace Nicolas Relun with:
Nicolas Relun France
Yicheng Zhou China
Harok Bae United States
Yishang Zhang China
Roland Schöbi Switzerland
Chengning Zhou China
Chuang Xiong China
Shui Yu China
Pierre Beaurepaire France
Hyunkyoo Cho relative to Nicolas Relun France Nicolas Relun's profile →
Citations per field
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Nicolas Relun · 1×
Citations per year

Countries citing papers authored by Hyunkyoo Cho

Since Specialization
Citations

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

Fields of papers citing papers by Hyunkyoo Cho

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Hyunkyoo Cho, 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 Hyunkyoo Cho Line = papers co-authored together Hyunkyoo Cho links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20246
2 20240
3 202411
4 20240
5 20240
6 20234
7 20213
8 202125
9 202016
10 201926
11 20194
12 201823
13 201836
14 201644
15 201620
16 20154
17 201512
18 201415
19 20136
20 20122

About Hyunkyoo Cho

Hyunkyoo Cho is a scholar working on Statistics, Probability and Uncertainty, Computational Theory and Mathematics and Safety, Risk, Reliability and Quality, having authored 43 papers that have together received 566 indexed citations. Recurring topics across this work include Probabilistic and Robust Engineering Design (36 papers), Advanced Multi-Objective Optimization Algorithms (27 papers), Optimal Experimental Design Methods (10 papers), Reliability and Maintenance Optimization (8 papers), Fatigue and fracture mechanics (6 papers), Cavitation Phenomena in Pumps (4 papers), Structural Health Monitoring Techniques (4 papers) and Statistical Distribution Estimation and Applications (3 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (398 citations), Computational Theory and Mathematics (272 citations) and Management Science and Operations Research (129 citations). Hyunkyoo Cho has collaborated with scholars based in South Korea, United States and China. Frequent co-authors include Kyung K. Choi, Ikjin Lee, Weifei Hu, David Lamb, Yongsu Jung, Nicholas J. Gaul, David Gorsich, Young‐Do Choi, Kyung‐Eun Lee and Seok-Heum Baek. Their work appears in journals such as SAE technical papers on CD-ROM/SAE technical paper series, IEEE Transactions on Magnetics and Structural and Multidisciplinary Optimization.

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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