Dae‐Kyoo Kim

1.8k citations
80 papers · 1.0k indexed · h-index 16
Topics
Software Engineering Research (35 papers)Advanced Software Engineering Methodologies (24 papers)Model-Driven Software Engineering Techniques (19 papers)
Journals
SHILAP Revista de lepidopterologíaIEEE Transactions on Power SystemsIEEE Communications Magazine

In The Last Decade

Dae‐Kyoo Kim

73 papers receiving 969 citations

Peers

Dae‐Kyoo Kim
Comparison fields: 5 of 73
  • Information Systems 694
  • Artificial Intelligence 613
  • Software 311
  • Computer Networks and Communications 251
  • Sociology and Political Science 106
Replace George T. Heineman with:
George T. Heineman United States
Welf Löwe Sweden
W. Kozaczynski United States
Marc Balcer United States
M. Blaha United States
Ali Mili United States
Brian Wilkerson United States
Mehmet Akşit Netherlands
Eila Niemelä Finland
Albert Zündorf Germany
Dae‐Kyoo Kim relative to George T. Heineman United States George T. Heineman's profile →
Citations per field
00.5×10×15×18.5×
George T. Heineman · 1×
Citations per year

Countries citing papers authored by Dae‐Kyoo Kim

Since Specialization
Citations

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

Fields of papers citing papers by Dae‐Kyoo Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dae‐Kyoo Kim. 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 Dae‐Kyoo Kim. The network helps show where Dae‐Kyoo Kim may publish in the future.

Co-authorship network of co-authors of Dae‐Kyoo Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Dae‐Kyoo Kim. A scholar is included among the top collaborators of Dae‐Kyoo Kim 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 Dae‐Kyoo Kim. Dae‐Kyoo Kim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 2
3 0
4 12
5 2
6 29
7 22
8 43
9 4
10 2
11 4
12 2
13 2
14 1
15 4
16 5
17 31
18 2
19 65
20 155

About Dae‐Kyoo Kim

Dae‐Kyoo Kim is a scholar working on Software, Information Systems and Development, having authored 80 papers that have together received 1.0k indexed citations. Recurring topics across this work include Software Engineering Research (35 papers), Advanced Software Engineering Methodologies (24 papers) and Model-Driven Software Engineering Techniques (19 papers). The work is most often cited by research in Software (311 citations), Information Systems (694 citations) and Artificial Intelligence (613 citations). Dae‐Kyoo Kim has collaborated with scholars based in United States, South Korea and China. Frequent co-authors include Sudipto Ghosh, Eun-Jee Song, Lunjin Lu, R.B. France, Robert France, Jo�ão Araújo, Sooyong Park, Dongwon Jeong, Hyo-Sik Yang and Suntae Kim. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Power Systems and IEEE Communications Magazine.

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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