Jaeyeon Jang

401 total citations
21 papers, 270 citations indexed

About

Jaeyeon Jang is a scholar working on Artificial Intelligence, Industrial and Manufacturing Engineering and Control and Systems Engineering. According to data from OpenAlex, Jaeyeon Jang has authored 21 papers receiving a total of 270 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 9 papers in Industrial and Manufacturing Engineering and 5 papers in Control and Systems Engineering. Recurrent topics in Jaeyeon Jang's work include Industrial Vision Systems and Defect Detection (8 papers), Fault Detection and Control Systems (3 papers) and Integrated Circuits and Semiconductor Failure Analysis (3 papers). Jaeyeon Jang is often cited by papers focused on Industrial Vision Systems and Defect Detection (8 papers), Fault Detection and Control Systems (3 papers) and Integrated Circuits and Semiconductor Failure Analysis (3 papers). Jaeyeon Jang collaborates with scholars based in South Korea and United States. Jaeyeon Jang's co-authors include Chang Ouk Kim, Byung Do Chung, Seyoung Park, Byung‐Wook Min, Kangjin Kim, Sinyoung Kim, Soon‐Jae Kwon, Ki Bum Lee, Xiuqi Li and Nital S. Patel and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and IEEE Transactions on Industrial Informatics.

In The Last Decade

Jaeyeon Jang

19 papers receiving 265 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jaeyeon Jang South Korea 11 117 75 67 65 65 21 270
Thomas Greiner Germany 11 86 0.7× 34 0.5× 120 1.8× 29 0.4× 107 1.6× 67 343
Richard Meyes Germany 9 104 0.9× 54 0.7× 46 0.7× 52 0.8× 13 0.2× 20 245
Kuihua Huang China 9 61 0.5× 120 1.6× 51 0.8× 23 0.4× 33 0.5× 41 258
M. Fi̇kret Ercan Singapore 7 269 2.3× 56 0.7× 29 0.4× 47 0.7× 21 0.3× 51 423
Yinzhi Zhou China 9 133 1.1× 275 3.7× 31 0.5× 53 0.8× 54 0.8× 19 495
Te-Sheng Li Taiwan 9 135 1.2× 40 0.5× 34 0.5× 21 0.3× 65 1.0× 11 243
Tarık Çakar Türkiye 10 97 0.8× 50 0.7× 54 0.8× 189 2.9× 12 0.2× 19 359
Ahmed Alsohaily Canada 7 38 0.3× 34 0.5× 23 0.3× 27 0.4× 262 4.0× 18 429
Yunqing Rao China 13 271 2.3× 39 0.5× 15 0.2× 30 0.5× 88 1.4× 36 422

Countries citing papers authored by Jaeyeon Jang

Since Specialization
Citations

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

Fields of papers citing papers by Jaeyeon Jang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jaeyeon Jang

This figure shows the co-authorship network connecting the top 25 collaborators of Jaeyeon Jang. A scholar is included among the top collaborators of Jaeyeon Jang 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 Jaeyeon Jang. Jaeyeon Jang 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.
Jang, Jaeyeon, et al.. (2025). Scalable multi-agent reinforcement learning for factory-wide dynamic scheduling in semiconductor manufacturing. Engineering Applications of Artificial Intelligence. 161. 112168–112168.
2.
Kwon, Soon‐Jae, et al.. (2024). Credit scoring using multi-task Siamese neural network for improving prediction performance and stability. Expert Systems with Applications. 259. 125327–125327. 5 indexed citations
3.
Jang, Jaeyeon, et al.. (2023). A test vector selection method based on machine learning for efficient presilicon verification. Expert Systems with Applications. 224. 120056–120056. 1 indexed citations
4.
Jang, Jaeyeon, et al.. (2023). Stepwise Soft Actor–Critic for UAV Autonomous Flight Control. Drones. 7(9). 549–549. 4 indexed citations
5.
Kim, Kangjin, et al.. (2023). Real-time path planning of controllable UAV by subgoals using goal-conditioned reinforcement learning. Applied Soft Computing. 146. 110660–110660. 16 indexed citations
6.
Jang, Jaeyeon, et al.. (2023). A two-stage semi-supervised object detection method for SAR images with missing labels based on meta pseudo-labels. Expert Systems with Applications. 236. 121405–121405. 8 indexed citations
7.
Jang, Jaeyeon & Chang Ouk Kim. (2023). Teacher–Explorer–Student Learning: A Novel Learning Method for Open Set Recognition. IEEE Transactions on Neural Networks and Learning Systems. 36(1). 767–780.
8.
Jang, Jaeyeon, et al.. (2022). Decision fusion approach for detecting unknown wafer bin map patterns based on a deep multitask learning model. Expert Systems with Applications. 215. 119363–119363. 8 indexed citations
9.
Jang, Jaeyeon, et al.. (2022). Sequential Residual Learning for Multistep Processes in Semiconductor Manufacturing. IEEE Transactions on Semiconductor Manufacturing. 36(1). 37–44. 7 indexed citations
10.
11.
Jang, Jaeyeon, et al.. (2022). Decision Fusion Approach for Detecting Unknown Wafer Bin Map Patterns Based on a Deep Multitask Learning Model. SSRN Electronic Journal. 1 indexed citations
12.
Jang, Jaeyeon & Chang Ouk Kim. (2022). Collective Decision of One-vs-Rest Networks for Open-Set Recognition. IEEE Transactions on Neural Networks and Learning Systems. 35(2). 2327–2338. 23 indexed citations
13.
Jang, Jaeyeon & Chang Ouk Kim. (2021). Unstructured borderline self-organizing map: Learning highly imbalanced, high-dimensional datasets for fault detection. Expert Systems with Applications. 188. 116028–116028. 14 indexed citations
14.
Jang, Jaeyeon & Chang Ouk Kim. (2021). Siamese Network-Based Health Representation Learning and Robust Reference-Based Remaining Useful Life Prediction. IEEE Transactions on Industrial Informatics. 18(8). 5264–5274. 32 indexed citations
15.
Park, Seyoung, Jaeyeon Jang, & Chang Ouk Kim. (2020). Discriminative feature learning and cluster-based defect label reconstruction for reducing uncertainty in wafer bin map labels. Journal of Intelligent Manufacturing. 32(1). 251–263. 33 indexed citations
16.
Jang, Jaeyeon & Byung Do Chung. (2020). Aggregate production planning considering implementation error: A robust optimization approach using bi-level particle swarm optimization. Computers & Industrial Engineering. 142. 106367–106367. 29 indexed citations
17.
Kim, Sinyoung, Jaeyeon Jang, & Chang Ouk Kim. (2020). A run-to-run controller for a chemical mechanical planarization process using least squares generative adversarial networks. Journal of Intelligent Manufacturing. 32(8). 2267–2280. 13 indexed citations
18.
Jang, Jaeyeon, Byung‐Wook Min, & Chang Ouk Kim. (2019). Denoised Residual Trace Analysis for Monitoring Semiconductor Process Faults. IEEE Transactions on Semiconductor Manufacturing. 32(3). 293–301. 22 indexed citations
19.
Jang, Jaeyeon, et al.. (2019). Adaptive Weapon-to-Target Assignment Model Based on the Real-Time Prediction of Hit Probability. IEEE Access. 7. 72210–72220. 14 indexed citations
20.
Lee, Ki Bum, et al.. (2017). Automatic inspection of salt-and-pepper defects in OLED panels using image processing and control chart techniques. Journal of Intelligent Manufacturing. 30(3). 1047–1055. 12 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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