Jaeha Kung

1.2k citations
51 papers · 827 indexed · h-index 15
Topics
Advanced Memory and Neural Computing (23 papers)Advanced Neural Network Applications (14 papers)Neural Networks and Applications (11 papers)
Partner nations
South KoreaUnited States

In The Last Decade

Jaeha Kung

46 papers receiving 797 citations

Peers

Jaeha Kung
Comparison fields: 5 of 57
  • Electrical and Electronic Engineering 536
  • Computer Vision and Pattern Recognition 305
  • Artificial Intelligence 230
  • Hardware and Architecture 223
  • Computer Networks and Communications 144
Replace Bert Moons with:
Bert Moons Belgium
Sae Kyu Lee United States
Jungwook Choi South Korea
Brian Zimmer United States
Paul N. Whatmough United States
Fengbin Tu China
Sanghoon Kang South Korea
Juhyoung Lee South Korea
Ben Keller United States
Jaeha Kung relative to Bert Moons Belgium Bert Moons's profile →
Citations per field
00.5×1.5×2.2×
Bert Moons · 1×
Citations per year

Countries citing papers authored by Jaeha Kung

Since Specialization
Citations

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

Fields of papers citing papers by Jaeha Kung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jaeha Kung

This figure shows the co-authorship network connecting the top 25 collaborators of Jaeha Kung. A scholar is included among the top collaborators of Jaeha Kung 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 Jaeha Kung. Jaeha Kung 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 0
2 1
3 0
4 2
5 1
6 15
7 1
8 2
9 0
10 21
11 9
12 2
13 1
14 27
15 38
16 5
17 12
18 29
19 246
20
Compact Thermal Models
5

About Jaeha Kung

Jaeha Kung is a scholar working on Computational Mathematics, Hardware and Architecture and Computer Vision and Pattern Recognition, having authored 51 papers that have together received 827 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (23 papers), Advanced Neural Network Applications (14 papers) and Neural Networks and Applications (11 papers). The work is most often cited by research in Hardware and Architecture (223 citations), Computational Mathematics (9 citations) and Computer Vision and Pattern Recognition (305 citations). Jaeha Kung has collaborated with scholars based in South Korea and United States. Frequent co-authors include Saibal Mukhopadhyay, Duck-Hwan Kim, Sek Chai, Sudhakar Yalamanchili, Youngjoo Lee, Jong Hwan Ko, Taesik Na, Jae‐Joon Kim, Yun Long and Youngsoo Shin. Their work appears in journals such as IEEE Access, IEEE Transactions on Computers and Frontiers in Neuroscience.

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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