Pilsung Kang

4.5k total citations · 3 hit papers
112 papers, 3.0k citations indexed

About

Pilsung Kang is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Pilsung Kang has authored 112 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Artificial Intelligence, 21 papers in Information Systems and 19 papers in Computer Vision and Pattern Recognition. Recurrent topics in Pilsung Kang's work include Topic Modeling (19 papers), Anomaly Detection Techniques and Applications (18 papers) and Industrial Vision Systems and Defect Detection (15 papers). Pilsung Kang is often cited by papers focused on Topic Modeling (19 papers), Anomaly Detection Techniques and Applications (18 papers) and Industrial Vision Systems and Defect Detection (15 papers). Pilsung Kang collaborates with scholars based in South Korea, United Kingdom and United States. Pilsung Kang's co-authors include Sungzoon Cho, Junhong Kim, Dong‐Hwa Kim, Dongil Kim, Seokho Kang, Hakyeon Lee, Seungwan Seo, Hyoungjoo Lee, Eenjun Hwang and Jihoon Moon and has published in prestigious journals such as Physical Review Letters, Nature Communications and Biomaterials.

In The Last Decade

Pilsung Kang

97 papers receiving 2.8k citations

Hit Papers

Multi-co-training for document classification using vario... 2018 2026 2020 2023 2018 2023 2024 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Multi-co-training for document classification using various document representations: TF–IDF, LDA, and Doc2Vec
    2018 313 citations Pilsung Kang et al. Information Sciences profile →
  2. Time-series anomaly detection with stacked Transformer representations and 1D convolutional network
    2023 106 citations Pilsung Kang et al. profile →
  3. Transformer-based multivariate time series anomaly detection using inter-variable attention mechanism
    2024 45 citations Pilsung Kang et al. Knowledge-Based Systems profile →

Peers

Pilsung Kang
J. Salvador Sánchez Spain
Xinheng Wang China
Lin Ma China
Guohua Wu China
Chunhua Zhang China
Shengding Hu China
Ganqu Cui China
Zhengyan Zhang China
Xiaochun Cheng United Kingdom
J. Salvador Sánchez Spain
Pilsung Kang
Citations per year, relative to Pilsung Kang Pilsung Kang (= 1×) peers J. Salvador Sánchez

Countries citing papers authored by Pilsung Kang

Since Specialization
Citations

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

Fields of papers citing papers by Pilsung Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pilsung Kang

This figure shows the co-authorship network connecting the top 25 collaborators of Pilsung Kang. A scholar is included among the top collaborators of Pilsung 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 Pilsung Kang. Pilsung 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.
Lee, Yukyung, et al.. (2025). CheckEval: A reliable LLM-as-a-Judge framework for evaluating text generation using checklists. 15782–15809. 1 indexed citations
2.
Han, S., et al.. (2025). Granularity Fusion Transformer: Learning multi-granularity patterns for time-series forecasting. Knowledge-Based Systems. 320. 113644–113644.
3.
Lee, Yukyung, et al.. (2024). DSTEA: Improving Dialogue State Tracking via Entity Adaptive pre-training. Knowledge-Based Systems. 290. 111542–111542. 3 indexed citations
4.
Kang, Pilsung, et al.. (2024). Multi-task self-supervised time-series representation learning. Information Sciences. 671. 120654–120654. 6 indexed citations
5.
Kang, Pilsung, et al.. (2024). RobustMixGen: Data augmentation for enhancing robustness of visual–language models in the presence of distribution shift. Neurocomputing. 619. 129167–129167. 1 indexed citations
6.
Kang, Pilsung, et al.. (2024). Normalizing flow-based latent space mapping for implicit pattern authentication on mobile devices. Applied Soft Computing. 169. 112469–112469. 1 indexed citations
7.
Seo, Seungwan, et al.. (2023). Exploring the differences in adversarial robustness between ViT- and CNN-based models using novel metrics. Computer Vision and Image Understanding. 235. 103800–103800. 14 indexed citations
8.
Kang, Pilsung, et al.. (2023). Fault classification and timing prediction based on shipment inspection data and maintenance reports for semiconductor manufacturing equipment. Computers & Industrial Engineering. 176. 108972–108972. 9 indexed citations
9.
Choi, Hee-Jeong, Subin Kim, & Pilsung Kang. (2023). Recurrent auto-encoder with multi-resolution ensemble and predictive coding for multivariate time-series anomaly detection. Applied Intelligence. 53(21). 25330–25342. 3 indexed citations
10.
Lee, Sangmin, et al.. (2023). Which is better? Exploring Prompting Strategy For LLM-based Metrics. 164–183. 5 indexed citations
11.
12.
Kang, Pilsung, et al.. (2022). K-Wav2vec 2.0: Automatic Speech Recognition based on Joint Decoding of Graphemes and Syllables. Interspeech 2022. 4945–4949. 3 indexed citations
13.
Kim, Junhong & Pilsung Kang. (2020). Freely typed keystroke dynamics-based user authentication for mobile devices based on heterogeneous features. Pattern Recognition. 108. 107556–107556. 37 indexed citations
14.
Kim, Junhong, et al.. (2019). Insider Threat Detection Based on User Behavior Modeling and Anomaly Detection Algorithms. Applied Sciences. 9(19). 4018–4018. 64 indexed citations
15.
Kang, Sungsam, Pilsung Kang, Tae-Seok Yang, et al.. (2017). High-resolution adaptive optical imaging within thick scattering media using closed-loop accumulation of single scattering. Nature Communications. 8(1). 2157–2157. 69 indexed citations
16.
Kim, Junhong, Hae‐Dong Kim, & Pilsung Kang. (2017). Keystroke dynamics-based user authentication using freely typed text based on user-adaptive feature extraction and novelty detection. Applied Soft Computing. 62. 1077–1087. 48 indexed citations
17.
Kang, Pilsung, et al.. (2015). TOLL FRAUD DETECTION OF VOIP SERVICES VIA AN ENSELBME OF NOVELTY DETECTION ALGORITHMS. International journal of industrial engineering. 22(2). 213–222. 1 indexed citations
18.
Kang, Pilsung, et al.. (2014). A Priority Analysis on Influential Factors for Invigorating Project Management Office (PMO) in Public Sectors based on Analytic Hierarchy Process (AHP). Journal of Society of Korea Industrial and Systems Engineering. 37(4). 42–53. 1 indexed citations
19.
Choi, Youngwoon, Tae-Seok Yang, Christopher Fang‐Yen, et al.. (2011). Overcoming the Diffraction Limit Using Multiple Light Scattering in a Highly Disordered Medium. Physical Review Letters. 107(2). 23902–23902. 240 indexed citations
20.
Kang, Pilsung & Sungzoon Cho. (2008). EUS SVMs: Ensemble of UnderSampled SVMs for Data Imbalance Problems. 7 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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