Daesung Kang

933 total citations
43 papers, 670 citations indexed

About

Daesung Kang is a scholar working on Condensed Matter Physics, Materials Chemistry and Electronic, Optical and Magnetic Materials. According to data from OpenAlex, Daesung Kang has authored 43 papers receiving a total of 670 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Condensed Matter Physics, 11 papers in Materials Chemistry and 10 papers in Electronic, Optical and Magnetic Materials. Recurrent topics in Daesung Kang's work include GaN-based semiconductor devices and materials (17 papers), ZnO doping and properties (11 papers) and Ga2O3 and related materials (10 papers). Daesung Kang is often cited by papers focused on GaN-based semiconductor devices and materials (17 papers), ZnO doping and properties (11 papers) and Ga2O3 and related materials (10 papers). Daesung Kang collaborates with scholars based in South Korea, United States and Japan. Daesung Kang's co-authors include Scott James, Tae‐Yeon Seong, Na Lae Eun, Jeong‐Ah Kim, Ji Hyun Youk, Eun Ju Son, Hye Mi Gweon, Daehyun Kim, Mingzhou Ding and Ji Eun Park and has published in prestigious journals such as Scientific Reports, Radiology and Optics Express.

In The Last Decade

Daesung Kang

38 papers receiving 654 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daesung Kang South Korea 13 220 188 117 97 93 43 670
Hojin Kim South Korea 16 293 1.3× 86 0.5× 182 1.6× 57 0.6× 148 1.6× 89 949
Zhihao Wu China 9 429 1.9× 55 0.3× 185 1.6× 11 0.1× 100 1.1× 16 1.0k
Rachel Sparks United Kingdom 19 428 1.9× 59 0.3× 153 1.3× 273 2.8× 8 0.1× 75 1.3k
David Mayerich United States 17 165 0.8× 100 0.5× 265 2.3× 43 0.4× 5 0.1× 80 1.1k
Vasileios Vavourakis United Kingdom 17 139 0.6× 26 0.1× 229 2.0× 13 0.1× 32 0.3× 52 691
Ryoichi Nakamura Japan 13 194 0.9× 87 0.5× 142 1.2× 22 0.2× 10 0.1× 84 697
Hanjung Song South Korea 12 110 0.5× 208 1.1× 208 1.8× 19 0.2× 10 0.1× 79 788
Raju Viswanathan United States 12 79 0.4× 183 1.0× 132 1.1× 24 0.2× 35 0.4× 29 859
Bradley D. Clymer United States 15 317 1.4× 105 0.6× 137 1.2× 46 0.5× 2 0.0× 61 747
Dahong Qian China 21 664 3.0× 70 0.4× 265 2.3× 14 0.1× 13 0.1× 61 1.3k

Countries citing papers authored by Daesung Kang

Since Specialization
Citations

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

Fields of papers citing papers by Daesung Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daesung Kang

This figure shows the co-authorship network connecting the top 25 collaborators of Daesung Kang. A scholar is included among the top collaborators of Daesung Kang 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 Daesung Kang. Daesung Kang 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.
Kang, Daesung, et al.. (2025). Efficient pretraining of ECG scalogram images using masked autoencoders for cardiovascular disease diagnosis. Scientific Reports. 15(1). 24444–24444.
2.
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Kang, Daesung, et al.. (2025). Self-distilled masked autoencoders for medical images. Engineering Applications of Artificial Intelligence. 160. 112055–112055.
4.
Kang, Daesung, et al.. (2024). Enhancing pediatric pneumonia diagnosis through masked autoencoders. Scientific Reports. 14(1). 6150–6150. 10 indexed citations
5.
Kang, Daesung, et al.. (2023). Multi-Modal Stacking Ensemble for the Diagnosis of Cardiovascular Diseases. Journal of Personalized Medicine. 13(2). 373–373. 37 indexed citations
6.
Kang, Daesung, et al.. (2023). Bimodal CNN for cardiovascular disease classification by co-training ECG grayscale images and scalograms. Scientific Reports. 13(1). 2937–2937. 28 indexed citations
7.
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Eun, Na Lae, Daesung Kang, Eun Ju Son, et al.. (2021). Texture analysis using machine learning–based 3-T magnetic resonance imaging for predicting recurrence in breast cancer patients treated with neoadjuvant chemotherapy. European Radiology. 31(9). 6916–6928. 15 indexed citations
9.
Kang, Daesung, Hye Mi Gweon, Na Lae Eun, et al.. (2021). A convolutional deep learning model for improving mammographic breast-microcalcification diagnosis. Scientific Reports. 11(1). 23925–23925. 12 indexed citations
10.
Kang, Daesung, et al.. (2019). Effect of unevenly-distributed V pits on the optical and electrical characteristics of green micro-light emitting diode. Journal of Physics D Applied Physics. 53(4). 45106–45106. 5 indexed citations
11.
Kang, Daesung, et al.. (2019). Structural Analysis of a Carriage Shuttle System : A Material Supply Device for Small-Scale Machine Tools. Journal of the Korean Society of Manufacturing Process Engineers. 18(4). 62–68. 3 indexed citations
12.
Kang, Daesung, Ji Eun Park, Young‐Hoon Kim, et al.. (2018). Diffusion radiomics as a diagnostic model for atypical manifestation of primary central nervous system lymphoma: development and multicenter external validation. Neuro-Oncology. 20(9). 1251–1261. 112 indexed citations
13.
14.
Park, Jae‐Seong, Jae Ho Kim, Daehyun Kim, et al.. (2017). Ag nanowire-based electrodes for improving the output power of ultraviolet AlGaN-based light-emitting diodes. Journal of Alloys and Compounds. 703. 198–203. 14 indexed citations
15.
Park, Jae‐Seong, Young Hoon Sung, Daesung Kang, et al.. (2017). Use of a patterned current blocking layer to enhance the light output power of InGaN-based light-emitting diodes. Optics Express. 25(15). 17556–17556. 11 indexed citations
16.
Kang, Daesung, et al.. (2016). Assessing Granger Causality in Electrophysiological Data: Removing the Adverse Effects of Common Signals via Bipolar Derivations. Frontiers in Systems Neuroscience. 9. 189–189. 48 indexed citations
17.
Park, Jae‐Seong, Jae Ho Kim, Daehyun Kim, et al.. (2016). Formation of an indium tin oxide nanodot/Ag nanowire electrode as a current spreader for near ultraviolet AlGaN-based light-emitting diodes. Nanotechnology. 28(4). 45205–45205. 12 indexed citations
18.
Kang, Daesung, Ki‐Young Song, Hwan-Hee Jeong, et al.. (2015). Comparison of the Performance of Lateral and Vertical InGaN/GaN-Based Light-Emitting Diodes with GaN and AlN Nucleation Layers. ECS Journal of Solid State Science and Technology. 5(2). Q1–Q6. 2 indexed citations
19.
Park, Jooyoung, Daesung Kang, Jong-Ho Kim, James T. Kwok, & Ivor W. Tsang. (2007). SVDD-Based Pattern Denoising. Neural Computation. 19(7). 1919–1938. 35 indexed citations
20.
Kang, Daesung, et al.. (2006). Pattern de-noising based on support vector data description. Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.. 2. 949–953. 6 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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