Suhyun Cha

435 citations
25 papers · 251 · h-index 6

Impact in

Papers in

Suhyun Cha

22 papers receiving 213 citations

Peers

Suhyun Cha
Comparison fields: 5 of 33
  • Software 144
  • Safety, Risk, Reliability and Quality 62
  • Statistics, Probability and Uncertainty 28
  • Hardware and Architecture 27
  • Industrial and Manufacturing Engineering 39
Replace Matthias Güdemann with:
Matthias Güdemann Germany
Mark‐Oliver Reiser Germany
Gilles Motet France
Charles B. Weinstock United States
David Servat France
Linas Laibinis Finland
C. Beounes France
M.A. Qureshi United States
Henrik Thane Sweden
Jean-Baptiste Raclet France
Suhyun Cha relative to Matthias Güdemann Germany Matthias Güdemann's profile →
Citations per field
00.5×3.7×
Matthias Güdemann · 1×
Citations per year

Countries citing papers authored by Suhyun Cha

Since Specialization
Citations

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

Fields of papers citing papers by Suhyun Cha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 17 scholars most cited alongside Suhyun Cha, 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 Suhyun Cha Line = papers co-authored together Suhyun Cha links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199092
2 199183
3 201811
4 201710
5 20178
6 20176
7 20185
8 20195
9 20175
10 20204
11 20194
12 20183
13 20093
14 20212
15 20122
16 20022
17 20181
18 20191
19 20171
20 20251

About Suhyun Cha

Suhyun Cha is a scholar working on Industrial and Manufacturing Engineering, Safety, Risk, Reliability and Quality, Software, Computational Theory and Mathematics and Computer Networks and Communications, having authored 25 papers that have together received 251 indexed citations. Recurring topics across this work include Flexible and Reconfigurable Manufacturing Systems (13 papers), Safety Systems Engineering in Autonomy (9 papers), Software Reliability and Analysis Research (7 papers), Manufacturing Process and Optimization (5 papers), Software Testing and Debugging Techniques (4 papers), Formal Methods in Verification (4 papers), Wireless Communication Networks Research (2 papers) and Software System Performance and Reliability (2 papers). The work is most often cited by research in Software (144 citations), Safety, Risk, Reliability and Quality (62 citations), Statistics, Probability and Uncertainty (28 citations), Hardware and Architecture (27 citations) and Industrial and Manufacturing Engineering (39 citations). Suhyun Cha has collaborated with scholars based in Germany, United States and South Korea. Frequent co-authors include Nancy G. Leveson, Timothy J. Shimeall, John Knight, Birgit Vogel‐Heuser, Mattias Ulbrich, Juliana Bowles, Robert Heinrich, Ralf Reussner, Bernhard Beckert and Emanuel Trunzer. Their work appears in journals such as IEEE Software, IEEE Transactions on Automation Science and Engineering, Journal of Pain, Science of Computer Programming and IEEE Transactions on Software Engineering.

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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