Yong-Kee Jun

408 citations
37 papers · 140 · h-index 7

Impact in

    • Parallel Computing and Optimization Techniques
    • Real-Time Systems Scheduling
    • Embedded Systems Design Techniques
  • Software top 10%
    • Software Testing and Debugging Techniques

Papers in

Yong-Kee Jun

33 papers receiving 137 citations

Peers

Yong-Kee Jun
Comparison fields: 5 of 30
  • Hardware and Architecture 99
  • Software 25
  • Computer Science Applications 19
  • Computer Networks and Communications 62
  • Health Information Management 5
Replace John Seng with:
John Seng United States
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Citations per year

Countries citing papers authored by Yong-Kee Jun

Since Specialization
Citations

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

Fields of papers citing papers by Yong-Kee Jun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yong-Kee Jun. 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 Yong-Kee Jun. The network helps show where Yong-Kee Jun may publish in the future.

Co-authors

The 13 scholars most cited alongside Yong-Kee Jun, 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 Yong-Kee Jun Line = papers co-authored together Yong-Kee Jun links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202324
2 201218
3 199312
4 20108
5 20157
6 20107
7 20146
8 20126
9 20155
10 20135
11 19985
12 20114
13 20084
14 20133
15 20143
16
On-the-fly Detection of the First Races in Programs with Nested Parallelism.
19962
17 20222
18 20152
19 20162
20 19932

About Yong-Kee Jun

Yong-Kee Jun is a scholar working on Hardware and Architecture, Computer Networks and Communications, Electrical and Electronic Engineering, Artificial Intelligence and Software, having authored 37 papers that have together received 140 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (25 papers), Real-Time Systems Scheduling (14 papers), Radiation Effects in Electronics (9 papers), Distributed systems and fault tolerance (8 papers), Embedded Systems Design Techniques (8 papers), Software Testing and Debugging Techniques (6 papers), Software System Performance and Reliability (5 papers) and Petri Nets in System Modeling (3 papers). The work is most often cited by research in Hardware and Architecture (99 citations), Software (25 citations), Computer Science Applications (19 citations), Computer Networks and Communications (62 citations) and Health Information Management (5 citations). Yong-Kee Jun has collaborated with scholars based in South Korea, United States and Canada. Frequent co-authors include Kyong Hoon Kim, Seongjin Lee, Kern Koh, Young-Joo Kim, Sejun Song, Hyunji Kim, Hee‐Dong Park, Junho Seo, Daeyoung Kim and Charles E. McDowell. Their work appears in journals such as Journal of Systems and Software, Applied Sciences, ACM SIGPLAN Notices, Journal of Systems Architecture and International Journal of Distributed Sensor Networks.

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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