Daekyum Kim

717 citations
23 papers · 464 indexed · h-index 11
Topics
Muscle activation and electromyography studies (7 papers)Stroke Rehabilitation and Recovery (5 papers)Advanced Sensor and Energy Harvesting Materials (5 papers)

In The Last Decade

Daekyum Kim

22 papers receiving 456 citations

Peers

Daekyum Kim
Comparison fields: 5 of 78
  • Biomedical Engineering 258
  • Computer Vision and Pattern Recognition 126
  • Control and Systems Engineering 111
  • Aerospace Engineering 81
  • Mechanical Engineering 64
Replace Anirban Mazumdar with:
Anirban Mazumdar United States
Yongzhuo Gao China
Matthew D. Lichter United States
Xu Liang China
Xuehe Zhang China
Matteo Russo Italy
Pierluigi Rea Italy
Baofeng Gao China
Yuquan Leng China
J. Jesús Cervantes‐Sánchez Mexico
Daekyum Kim relative to Anirban Mazumdar United States Anirban Mazumdar's profile →
Citations per field
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Anirban Mazumdar · 1×
Citations per year

Countries citing papers authored by Daekyum Kim

Since Specialization
Citations

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

Fields of papers citing papers by Daekyum Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daekyum Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Daekyum Kim. A scholar is included among the top collaborators of Daekyum 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 Daekyum Kim. Daekyum 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 2
2 5
3 1
4 1
5 16
6 8
7 2
8 11
9 1
10 2
11 23
12 10
13 175
14 9
15 21
16 3
17 16
18 28
19 8
20 74

About Daekyum Kim

Daekyum Kim is a scholar working on Rehabilitation, Physical Therapy, Sports Therapy and Rehabilitation and Computer Vision and Pattern Recognition, having authored 23 papers that have together received 464 indexed citations. Recurring topics across this work include Muscle activation and electromyography studies (7 papers), Stroke Rehabilitation and Recovery (5 papers) and Advanced Sensor and Energy Harvesting Materials (5 papers). The work is most often cited by research in Rehabilitation (47 citations), Computer Vision and Pattern Recognition (126 citations) and Biomedical Engineering (258 citations). Daekyum Kim has collaborated with scholars based in South Korea, United States and United Kingdom. Frequent co-authors include Sungho Jo, Soohwan Song, Kyu‐Jin Cho, Brian Byunghyun Kang, Sunghee Choi, Hyungmin Choi, Wookeun Park, Junghan Kwon, DongWook Kim and Yong‐Lae Park. Their work appears in journals such as Nature Communications, PLoS ONE and Advanced Functional Materials.

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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