Chun-Kwon Lee

493 total citations
25 papers, 355 citations indexed

About

Chun-Kwon Lee is a scholar working on Electrical and Electronic Engineering, Control and Systems Engineering and Civil and Structural Engineering. According to data from OpenAlex, Chun-Kwon Lee has authored 25 papers receiving a total of 355 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Electrical and Electronic Engineering, 13 papers in Control and Systems Engineering and 6 papers in Civil and Structural Engineering. Recurrent topics in Chun-Kwon Lee's work include Electrical Fault Detection and Protection (20 papers), Integrated Circuits and Semiconductor Failure Analysis (14 papers) and Concrete Corrosion and Durability (6 papers). Chun-Kwon Lee is often cited by papers focused on Electrical Fault Detection and Protection (20 papers), Integrated Circuits and Semiconductor Failure Analysis (14 papers) and Concrete Corrosion and Durability (6 papers). Chun-Kwon Lee collaborates with scholars based in South Korea, United States and Germany. Chun-Kwon Lee's co-authors include Yong–June Shin, Gu-Young Kwon, Seung Jin Chang, Yeong Ho Lee, Geon Seok Lee, Ji-Won Kang, Jin Bae Park, Ju-Yong Kim, Hansoo Kim and Hee Cho and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, IEEE Access and IEEE Transactions on Power Delivery.

In The Last Decade

Chun-Kwon Lee

23 papers receiving 350 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Chun-Kwon Lee South Korea 10 289 156 85 67 36 25 355
Seung Jin Chang South Korea 10 265 0.9× 152 1.0× 72 0.8× 55 0.8× 35 1.0× 29 341
Bowen Jia China 9 187 0.6× 173 1.1× 22 0.3× 44 0.7× 48 1.3× 22 334
Qiuyu Yang China 10 199 0.7× 199 1.3× 17 0.2× 23 0.3× 36 1.0× 30 307
Kun Yu China 12 371 1.3× 301 1.9× 15 0.2× 22 0.3× 49 1.4× 84 450
Moussa Kafal France 10 354 1.2× 179 1.1× 66 0.8× 10 0.1× 19 0.5× 28 418
Pengju Kang Australia 10 348 1.2× 155 1.0× 23 0.3× 90 1.3× 28 0.8× 14 429
Özcan Kalenderli Türkiye 10 239 0.8× 90 0.6× 19 0.2× 182 2.7× 15 0.4× 63 329
Mian Wang China 11 232 0.8× 143 0.9× 50 0.6× 17 0.3× 19 0.5× 47 405
Levy Ely de Lacerda de Oliveira Brazil 9 156 0.5× 333 2.1× 33 0.4× 49 0.7× 232 6.4× 26 449
Jong-Ho Sun South Korea 9 119 0.4× 205 1.3× 57 0.7× 103 1.5× 135 3.8× 27 344

Countries citing papers authored by Chun-Kwon Lee

Since Specialization
Citations

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

Fields of papers citing papers by Chun-Kwon Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chun-Kwon 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 Chun-Kwon Lee. The network helps show where Chun-Kwon Lee may publish in the future.

Co-authorship network of co-authors of Chun-Kwon Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Chun-Kwon Lee. A scholar is included among the top collaborators of Chun-Kwon Lee 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 Chun-Kwon Lee. Chun-Kwon Lee 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
1.
Park, Hwa-Pyeong, Gu-Young Kwon, Chun-Kwon Lee, & Seung Jin Chang. (2024). AI-enhanced time–frequency domain reflectometry for robust series arc fault detection in DC grids. Measurement. 238. 115188–115188. 6 indexed citations
2.
Lee, Chun-Kwon, et al.. (2024). AI-based remaining useful life prediction for transmission systems: Integrating operating conditions with TimeGAN and CNN-LSTM networks. Electric Power Systems Research. 238. 111151–111151. 2 indexed citations
3.
Chang, Seung Jin, Gu-Young Kwon, & Chun-Kwon Lee. (2024). Assessment of Cable Degradation Using Reflectometry-Based Dielectric Loss Estimation. IEEE Transactions on Instrumentation and Measurement. 73. 1–9. 1 indexed citations
4.
Cho, Hee, et al.. (2023). Ensemble-NQG-T5: Ensemble Neural Question Generation Model Based on Text-to-Text Transfer Transformer. Applied Sciences. 13(2). 903–903. 17 indexed citations
5.
Kim, Woo Hyun, et al.. (2023). Active TCC based protection coordination scheme for networked distribution system. International Journal of Electrical Power & Energy Systems. 153. 109341–109341. 4 indexed citations
6.
Lee, Chun-Kwon, et al.. (2022). Cable fault and assessment using multiple frequency autoencoder regression-based reflectometry. IEICE Electronics Express. 19(17). 20220113–20220113. 1 indexed citations
7.
Lee, Chun-Kwon, et al.. (2021). Flexible Multi Sensor Monitoring System for Medium Voltage Cable Joints. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 1–4. 1 indexed citations
8.
Lee, Chun-Kwon, Gyu‐Sub Lee, & Seung Jin Chang. (2021). Solution to Fault of Multi-Terminal DC Transmission Systems Based on High Temperature Superconducting DC Cables. Energies. 14(5). 1292–1292. 3 indexed citations
9.
Lee, Chun-Kwon & Seung Jin Chang. (2020). A Method of Fault Localization Within the Blind Spot Using the Hybridization Between TDR and Wavelet Transform. IEEE Sensors Journal. 21(4). 5102–5110. 21 indexed citations
10.
Lee, Chun-Kwon & Yong–June Shin. (2020). Detection and Assessment of I&C Cable Faults Using Time–Frequency R-CNN-Based Reflectometry. IEEE Transactions on Industrial Electronics. 68(2). 1581–1590. 20 indexed citations
11.
Lee, Chun-Kwon & Seung Jin Chang. (2019). Fault Detection in Multi-Core C&I Cable via Machine Learning Based Time-Frequency Domain Reflectometry. Applied Sciences. 10(1). 158–158. 15 indexed citations
12.
Lee, Geon Seok, et al.. (2018). A Statistical Approach in Time-Frequency Domain Reflectometry for Enhanced Fault Detection. 2018 IEEE 2nd International Conference on Dielectrics (ICD). 993. 1–4.
13.
Lee, Chun-Kwon & Yong–June Shin. (2018). Multi-core cable fault diagnosis using cluster time-frequency domain reflectometry. 20. 1–6. 5 indexed citations
14.
Kwon, Gu-Young, Chun-Kwon Lee, Geon Seok Lee, et al.. (2018). Offline Fault Localization Technique on HVDC Submarine Cable via Time-Frequency Domain Reflectometry. 1–1. 1 indexed citations
15.
Lee, Chun-Kwon, Gu-Young Kwon, & Yong–June Shin. (2018). Condition Assessment of I&C Cables in Nuclear Power Plants via Stepped-Frequency Waveform Reflectometry. IEEE Transactions on Instrumentation and Measurement. 68(1). 215–224. 41 indexed citations
16.
Lee, Yeong Ho, et al.. (2018). Application of Inductive Coupler for Diagnosis of Live Cable System. 2018 IEEE 2nd International Conference on Dielectrics (ICD). 17. 1–3. 2 indexed citations
17.
Kwon, Gu-Young, Chun-Kwon Lee, Geon Seok Lee, et al.. (2017). Offline Fault Localization Technique on HVDC Submarine Cable via Time–Frequency Domain Reflectometry. IEEE Transactions on Power Delivery. 32(3). 1626–1635. 85 indexed citations
18.
Bang, Su Sik, Geon Seok Lee, Gu-Young Kwon, et al.. (2016). Modeling and simulation of HTS cables for scattering parameter analysis. Physica C Superconductivity. 530. 142–146. 4 indexed citations
19.
Chang, Seung Jin, et al.. (2015). Condition Monitoring of Instrumentation Cable Splices Using Kalman Filtering. IEEE Transactions on Instrumentation and Measurement. 64(12). 3490–3499. 18 indexed citations
20.
Lee, Chun-Kwon, et al.. (2013). Diagnosis of cables in nuclear power plants using joint time-frequency domain reflectometry. IFAC Proceedings Volumes. 46(29). 74–78. 3 indexed citations

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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