Seokho Kang

2.3k total citations
84 papers, 1.6k citations indexed

About

Seokho Kang is a scholar working on Artificial Intelligence, Industrial and Manufacturing Engineering and Electrical and Electronic Engineering. According to data from OpenAlex, Seokho Kang has authored 84 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Artificial Intelligence, 24 papers in Industrial and Manufacturing Engineering and 19 papers in Electrical and Electronic Engineering. Recurrent topics in Seokho Kang's work include Industrial Vision Systems and Defect Detection (24 papers), Computational Drug Discovery Methods (15 papers) and Imbalanced Data Classification Techniques (14 papers). Seokho Kang is often cited by papers focused on Industrial Vision Systems and Defect Detection (24 papers), Computational Drug Discovery Methods (15 papers) and Imbalanced Data Classification Techniques (14 papers). Seokho Kang collaborates with scholars based in South Korea, United States and Canada. Seokho Kang's co-authors include Sungzoon Cho, Pilsung Kang, Youn-Suk Choi, Youngchun Kwon, Kyunghyun Cho, Dongseon Lee, Hyungu Kang, Dongil Kim, Inkoo Kim and Won‐Joon Son and has published in prestigious journals such as Analytical Chemistry, Scientific Reports and Physical Chemistry Chemical Physics.

In The Last Decade

Seokho Kang

82 papers receiving 1.6k citations

Peers

Seokho Kang

IME

CTM

EEE

M. Srinivas India

Kangshun Li China

Yiping Liu China

Zhenyu Lu China

Oliver Krämer Germany

Yuan Sun China

Lihong Guo China

Francisco B. Pereira Portugal

Chrysanthos E. Gounaris United States

Xi Chen China

M. Srinivas India

Seokho Kang

146 ×0.3

IME

641 ×1.6

143 ×0.4

270 ×0.8

CTM

425 ×1.3

EEE

Citations per year, relative to Seokho Kang Seokho Kang (= 1×) peers M. Srinivas

Countries citing papers authored by Seokho Kang

Since Specialization

Citations

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

Fields of papers citing papers by Seokho Kang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Seokho Kang

This figure shows the co-authorship network connecting the top 25 collaborators of Seokho Kang. A scholar is included among the top collaborators of Seokho 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 Seokho Kang. Seokho Kang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Kang, Seokho, et al.. (2025). Consistency-regularized graph neural networks for molecular property prediction. Neural Networks. 194. 108157–108157.

Kang, Seokho, et al.. (2025). Why does this query need to be labeled?: Enhancing active learning through explanation-based interventions in query selection. Expert Systems with Applications. 290. 128443–128443.

Kang, Seokho, et al.. (2024). CFD-ML: Stream-based active learning of computational fluid dynamics simulations for efficient product design. Computers in Industry. 161. 104122–104122. 7 indexed citations

Kang, Seokho, et al.. (2024). Predicting early mycotoxin contamination in stored wheat using machine learning. Journal of Stored Products Research. 106. 102294–102294. 14 indexed citations

Kang, Seokho, et al.. (2024). Score distillation for anomaly detection. Knowledge-Based Systems. 295. 111842–111842. 2 indexed citations

Kang, Seokho, et al.. (2024). Knowledge distillation with insufficient training data for regression. Engineering Applications of Artificial Intelligence. 132. 108001–108001. 2 indexed citations

Kang, Seokho, et al.. (2023). Supervised contrastive learning for wafer map pattern classification. Engineering Applications of Artificial Intelligence. 126. 107154–107154. 14 indexed citations

Kang, Seokho, et al.. (2023). Learning from single-defect wafer maps to classify mixed-defect wafer maps. Expert Systems with Applications. 233. 120923–120923. 15 indexed citations

Kang, Seokho, et al.. (2023). Optimization of missing value imputation for neural networks. Information Sciences. 649. 119668–119668. 2 indexed citations

10.

Kang, Seokho, et al.. (2023). Efficient improvement of classification accuracy via selective test-time augmentation. Information Sciences. 642. 119148–119148. 5 indexed citations

11.

Kang, Seokho, et al.. (2023). Surrogate approach to uncertainty quantification of neural networks for regression. Applied Soft Computing. 139. 110234–110234. 5 indexed citations

12.

Kang, Hyungu & Seokho Kang. (2023). Semi-supervised rotation-invariant representation learning for wafer map pattern analysis. Engineering Applications of Artificial Intelligence. 120. 105864–105864. 8 indexed citations

13.

Kang, Seokho, et al.. (2022). Dynamic imputation for improved training of neural network with missing values. Expert Systems with Applications. 194. 116508–116508. 13 indexed citations

14.

Kwon, Youngchun, Seokho Kang, Youn-Suk Choi, & Inkoo Kim. (2021). Evolutionary design of molecules based on deep learning and a genetic algorithm. Scientific Reports. 11(1). 17304–17304. 30 indexed citations

15.

Kwon, Youngchun, Dongseon Lee, Youn-Suk Choi, & Seokho Kang. (2021). Molecular search by NMR spectrum based on evaluation of matching between spectrum and molecule. Scientific Reports. 11(1). 20998–20998. 7 indexed citations

16.

Park, Jong-Ho, et al.. (2020). Unsupervised Anomaly Detection Using Style Distillation. IEEE Access. 8. 221494–221502. 18 indexed citations

17.

Kwon, Youngchun, et al.. (2020). Compressed graph representation for scalable molecular graph generation. Journal of Cheminformatics. 12(1). 58–58. 26 indexed citations

18.

Kwon, Youngchun, Jiho Yoo, Youn-Suk Choi, et al.. (2019). Efficient learning of non-autoregressive graph variational autoencoders for molecular graph generation. Journal of Cheminformatics. 11(1). 70–70. 47 indexed citations

19.

Kang, Seokho. (2018). Personalized prediction of drug efficacy for diabetes treatment via patient-level sequential modeling with neural networks. Artificial Intelligence in Medicine. 85. 1–6. 18 indexed citations

20.

Kim, Misuk, et al.. (2017). Virtual metrology for copper-clad laminate manufacturing. Computers & Industrial Engineering. 109. 280–287. 17 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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