Kang‐Dae Lee

834 citations
42 papers · 604 · h-index 15

Impact in

Papers in

Kang‐Dae Lee

42 papers receiving 586 citations

Peers

Kang‐Dae Lee
Comparison fields: 5 of 110
  • Industrial and Manufacturing Engineering 117
  • Transportation 60
  • Anesthesiology and Pain Medicine 45
  • Strategy and Management 116
  • Industrial and Manufacturing Engineering 50
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Gang Du China
Mandeep Mittal India
Tuncay Özcan Türkiye
Santonab Chakraborty India
Chun Jin China
Ajith Tom James India
Zhijie Dong China
Fangfang Wei China
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Citations per field
00.5×3.6×
Gang Du · 1×
Citations per year

Countries citing papers authored by Kang‐Dae Lee

Since Specialization
Citations

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

Fields of papers citing papers by Kang‐Dae Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Kang‐Dae Lee, 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 Kang‐Dae Lee Line = papers co-authored together Kang‐Dae Lee links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200956
2 201749
3 201238
4 201737
5 200335
6 201334
7 200732
8 201630
9 201330
10 201724
11
Body fluid biomarkers for early detection of head and neck squamous cell carcinomas.
201123
12 201623
13 201322
14 201319
15 201916
16 201913
17 201112
18 201312
19 20099
20 20139

About Kang‐Dae Lee

Kang‐Dae Lee is a scholar working on Industrial and Manufacturing Engineering, Building and Construction, Transportation, Automotive Engineering and Biomedical Engineering, having authored 42 papers that have together received 604 indexed citations. Recurring topics across this work include Maritime Ports and Logistics (11 papers), Urban and Freight Transport Logistics (11 papers), Transportation Planning and Optimization (9 papers), Advanced Manufacturing and Logistics Optimization (5 papers), Vehicle emissions and performance (3 papers), Sustainable Supply Chain Management (3 papers), Transportation and Mobility Innovations (3 papers) and Thyroid and Parathyroid Surgery (3 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (117 citations), Transportation (60 citations), Anesthesiology and Pain Medicine (45 citations), Strategy and Management (116 citations) and Industrial and Manufacturing Engineering (50 citations). Kang‐Dae Lee has collaborated with scholars based in South Korea, United States and Taiwan. Frequent co-authors include Kyungyong Chung, Sung Young Park, Insik In, Hyun-Soo Kim, Dongjoo Park, Eun Bi Kang, Zihnil Adha Islamy Mazrad, Chang‐Ho Jeon, Youngho Lee and Mitsuo Gen. Their work appears in journals such as Multimedia Tools and Applications, Personal and Ubiquitous Computing, International Journal of Sustainable Transportation, Journal of Advanced Transportation and Sustainability.

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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