Soo-Yeon Ji

734 total citations
56 papers, 507 citations indexed

About

Soo-Yeon Ji is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Soo-Yeon Ji has authored 56 papers receiving a total of 507 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 12 papers in Computer Vision and Pattern Recognition and 11 papers in Computer Networks and Communications. Recurrent topics in Soo-Yeon Ji's work include Network Security and Intrusion Detection (11 papers), Anomaly Detection Techniques and Applications (9 papers) and Internet Traffic Analysis and Secure E-voting (8 papers). Soo-Yeon Ji is often cited by papers focused on Network Security and Intrusion Detection (11 papers), Anomaly Detection Techniques and Applications (9 papers) and Internet Traffic Analysis and Secure E-voting (8 papers). Soo-Yeon Ji collaborates with scholars based in United States, Norway and Puerto Rico. Soo-Yeon Ji's co-authors include Dong Hyun Jeong, Kayvan Najarian, Kevin R. Ward, Rebecca Smith, Byunggu Yu, Wenan Chen, Toan Huynh, Claude Turner, Sharad Sharma and Charles Kamhoua and has published in prestigious journals such as Circulation, SHILAP Revista de lepidopterología and NeuroImage.

In The Last Decade

Soo-Yeon Ji

53 papers receiving 482 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Soo-Yeon Ji United States	11	232	177	83	81	63	56	507
Sadaqat Ur Rehman United Kingdom	7	134 0.6×	152 0.9×	41 0.5×	94 1.2×	43 0.7×	22	382
N. Sarshar Iran	12	187 0.8×	206 1.2×	154 1.9×	66 0.8×	41 0.7×	29	707
Sidra Abbas Pakistan	14	303 1.3×	233 1.3×	99 1.2×	82 1.0×	50 0.8×	29	714
Haya Alaskar Saudi Arabia	15	192 0.8×	108 0.6×	109 1.3×	69 0.9×	93 1.5×	36	676
Jiangang Ma Australia	11	168 0.7×	77 0.4×	55 0.7×	56 0.7×	54 0.9×	29	468
Chaoyi Pang China	15	268 1.2×	83 0.5×	300 3.6×	129 1.6×	80 1.3×	61	647
Oumaima Saidani Saudi Arabia	15	200 0.9×	57 0.3×	113 1.4×	41 0.5×	33 0.5×	58	521
Fatima Alshehri Saudi Arabia	4	113 0.5×	120 0.7×	75 0.9×	20 0.2×	55 0.9×	6	420
Nasmin Jiwani United States	14	100 0.4×	89 0.5×	42 0.5×	27 0.3×	30 0.5×	37	446
Saadullah Farooq Abbasi United Kingdom	13	92 0.4×	56 0.3×	105 1.3×	57 0.7×	70 1.1×	34	450

Countries citing papers authored by Soo-Yeon Ji

Since Specialization

Citations

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

Fields of papers citing papers by Soo-Yeon Ji

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Soo-Yeon Ji. 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 Soo-Yeon Ji. The network helps show where Soo-Yeon Ji may publish in the future.

Co-authorship network of co-authors of Soo-Yeon Ji

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Kim, Minjun, Soo-Yeon Ji, Hyeong‐Geol Shin, et al.. (2025). In-vivo high-resolution χ-separation at 7T. NeuroImage. 308. 121060–121060.

Jeong, Dong Hyun, et al.. (2024). Leveraging Machine Learning to Analyze Semantic User Interactions in Visual Analytics. Information. 15(6). 351–351. 1 indexed citations

Ji, Soo-Yeon, et al.. (2023). An Analysis of Temporal Features in Multivariate Time Series to Forecast Network Events. Applied Sciences. 13(18). 10411–10411. 1 indexed citations

Jeong, Dong Hyun, et al.. (2023). Multi-Resolution Analysis with Visualization to Determine Network Attack Patterns. Applied Sciences. 13(6). 3792–3792. 4 indexed citations

Ji, Soo-Yeon, et al.. (2023). Identifying Patterns for Neurological Disabilities by Integrating Discrete Wavelet Transform and Visualization. Applied Sciences. 14(1). 273–273. 3 indexed citations

Shin, Hyeong‐Geol, Riccardo Galbusera, Jincheol Seo, et al.. (2023). Imaging multiple sclerosis histopathology using susceptibility source separation: a postmortem brain study. Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition. 2 indexed citations

Jeong, Dong Hyun, et al.. (2022). Designing a supervised feature selection technique for mixed attribute data analysis. SHILAP Revista de lepidopterología. 10. 100431–100431. 8 indexed citations

Jeong, Dong Hyun, Jin-Hee Cho, Feng Chen, et al.. (2022). Interactive Web-Based Visual Analysis on Network Traffic Data. Information. 14(1). 16–16. 2 indexed citations

Ji, Soo-Yeon, et al.. (2021). Lean IT With Value Stream Mapping Analysis. Information Resources Management Journal. 35(1). 1–18.

10.

Ji, Soo-Yeon, et al.. (2020). Evaluating visualization approaches to detect abnormal activities in network traffic data. International Journal of Information Security. 20(3). 331–345. 17 indexed citations

11.

Ji, Soo-Yeon, et al.. (2019). An Analysis of Human Emotions by Utilizing Wavelet Features. RePEc: Research Papers in Economics. 10(4). 46–63. 1 indexed citations

12.

Ji, Soo-Yeon, Charles Kamhoua, Nandi Leslie, & Dong Hyun Jeong. (2019). An Effective Approach to Classify Abnormal Network Traffic Activities using Wavelet Transform. 666–672. 3 indexed citations

13.

Ji, Soo-Yeon, Dong Hyun Jeong, Moinuddin Hassan, & Ilko K. Ilev. (2018). Signature Infrared Bacteria Spectra Analyzed by an Advanced Integrative Computational Approach Developed for Identifying Bacteria Similarity. IEEE Journal of Selected Topics in Quantum Electronics. 25(1). 1–8. 9 indexed citations

14.

Ji, Soo-Yeon, et al.. (2016). A survey of cloud-based network intrusion detection analysis. Human-centric Computing and Information Sciences. 6(1). 66 indexed citations

15.

Ji, Soo-Yeon, et al.. (2015). Cloud-Scale Genomic Signals Processing for Robust Large-Scale Cancer Genomic Microarray Data Analysis. IEEE Journal of Biomedical and Health Informatics. 21(1). 238–245. 7 indexed citations

16.

Ji, Soo-Yeon, Ashwin Belle, Kevin R. Ward, et al.. (2013). Heart rate variability analysis during central hypovolemia using wavelet transformation. Journal of Clinical Monitoring and Computing. 27(3). 289–302. 13 indexed citations

17.

Ji, Soo-Yeon, et al.. (2010). Abstract 242: Prediction of Shock Outcome Using Signal Processing and Machine Learning. Circulation. 122. 117203–117203. 1 indexed citations

18.

Ji, Soo-Yeon, et al.. (2009). Abstract P115: Prediction of Severity of Blood Volume Loss Using ECG Features Based on P, QRS, and T Waves. Circulation. 120. 1 indexed citations

19.

Ji, Soo-Yeon, Rebecca Smith, Toan Huynh, & Kayvan Najarian. (2009). A comparative analysis of multi-level computer-assisted decision making systems for traumatic injuries. BMC Medical Informatics and Decision Making. 9(1). 2–2. 31 indexed citations

20.

Chen, Wenan, Rebecca Smith, Soo-Yeon Ji, Kevin R. Ward, & Kayvan Najarian. (2009). Automated ventricular systems segmentation in brain CT images by combining low-level segmentation and high-level template matching. BMC Medical Informatics and Decision Making. 9(S1). S4–S4. 58 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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