Ming‐Yang Su

1.7k total citations · 1 hit paper
52 papers, 1.1k citations indexed

About

Ming‐Yang Su is a scholar working on Computer Networks and Communications, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Ming‐Yang Su has authored 52 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Computer Networks and Communications, 20 papers in Artificial Intelligence and 13 papers in Signal Processing. Recurrent topics in Ming‐Yang Su's work include Network Security and Intrusion Detection (22 papers), Advanced Malware Detection Techniques (13 papers) and Internet Traffic Analysis and Secure E-voting (10 papers). Ming‐Yang Su is often cited by papers focused on Network Security and Intrusion Detection (22 papers), Advanced Malware Detection Techniques (13 papers) and Internet Traffic Analysis and Secure E-voting (10 papers). Ming‐Yang Su collaborates with scholars based in Taiwan, United States and China. Ming‐Yang Su's co-authors include Shi‐Jinn Horng, Y-H. Chen, Rong‐Jian Chen, Tzong‐Wann Kao, Jui‐Lin Lai, Gwo‐Jong Yu, Dyi‐Rong Duh, Gen-Huey Chen, Wei-Cheng Liao and Jang‐Ping Sheu and has published in prestigious journals such as Expert Systems with Applications, Sensors and Applied Sciences.

In The Last Decade

Ming‐Yang Su

46 papers receiving 989 citations

Hit Papers

A novel intrusion detection system based on hierarchical ... 2010 2026 2015 2020 2010 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. A novel intrusion detection system based on hierarchical clustering and support vector machines
    2010 332 citations Shi‐Jinn Horng, Ming‐Yang Su et al. Expert Systems with Applications profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ming‐Yang Su Taiwan 15 850 524 330 183 177 52 1.1k
Muddassar Farooq Pakistan 19 979 1.2× 370 0.7× 440 1.3× 285 1.6× 279 1.6× 55 1.3k
Nasser Yazdani Iran 17 842 1.0× 442 0.8× 228 0.7× 312 1.7× 178 1.0× 97 1.2k
Emin Anarım Türkiye 16 816 1.0× 586 1.1× 407 1.2× 184 1.0× 132 0.7× 118 1.2k
Hasan Çam United States 18 864 1.0× 244 0.5× 134 0.4× 188 1.0× 235 1.3× 89 1.1k
Anwar Haque Canada 15 758 0.9× 530 1.0× 285 0.9× 152 0.8× 222 1.3× 90 1.1k
Animesh Patcha United States 7 1.2k 1.4× 768 1.5× 378 1.1× 156 0.9× 170 1.0× 11 1.5k
Zhiliang Wang China 22 1.4k 1.6× 763 1.5× 309 0.9× 194 1.1× 337 1.9× 155 1.8k
Muhammad Sher Pakistan 19 1.1k 1.3× 586 1.1× 231 0.7× 629 3.4× 244 1.4× 86 1.4k
Kangbin Yim South Korea 18 818 1.0× 365 0.7× 720 2.2× 533 2.9× 205 1.2× 111 1.3k
Mqhele E. Dlodlo South Africa 9 725 0.9× 350 0.7× 234 0.7× 272 1.5× 178 1.0× 57 911

Countries citing papers authored by Ming‐Yang Su

Since Specialization
Citations

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

Fields of papers citing papers by Ming‐Yang Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ming‐Yang Su. 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 Ming‐Yang Su. The network helps show where Ming‐Yang Su may publish in the future.

Co-authorship network of co-authors of Ming‐Yang Su

This figure shows the co-authorship network connecting the top 25 collaborators of Ming‐Yang Su. A scholar is included among the top collaborators of Ming‐Yang Su 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 Ming‐Yang Su. Ming‐Yang Su 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.
Chang, Chih-Yung, et al.. (2025). Toward Interpretable Multimodal Violence Detection With Knowledge Distillation and Modality-Aligned Preprocessing. IEEE Transactions on Systems Man and Cybernetics Systems. 55(9). 6215–6228.
2.
Su, Ming‐Yang, et al.. (2025). Toward Enabling Natural Conversation with Older Adults via the Design of LLM-Powered Voice Agents that Support Interruptions and Backchannels. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 1–22. 2 indexed citations
3.
Su, Ming‐Yang, et al.. (2024). Toward Facilitating Search in VR With the Assistance of Vision Large Language Models. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 1–14. 1 indexed citations
4.
5.
Liu, Haiyang, Zihao Zhu, Ming‐Yang Su, et al.. (2024). EMAGE: Towards Unified Holistic Co-Speech Gesture Generation via Expressive Masked Audio Gesture Modeling. 1144–1154. 23 indexed citations
6.
Su, Ming‐Yang, et al.. (2023). BERT-Based Approaches to Identifying Malicious URLs. Sensors. 23(20). 8499–8499. 19 indexed citations
7.
8.
Chang, Chih‐Yung, et al.. (2022). On-Demand Recharge Scheduling Algorithm in Wireless Sensor Networks. 13–17. 2 indexed citations
9.
Su, Ming‐Yang, et al.. (2019). Android Malware Detection Approaches in Combination with Static and Dynamic Features.. Int. J. Netw. Secur.. 21. 1031–1041. 1 indexed citations
10.
Su, Ming‐Yang & Chen‐Han Tsai. (2013). Using data mining approaches to identify voice over IP spam. International Journal of Communication Systems. 28(1). 187–200. 6 indexed citations
11.
Su, Ming‐Yang. (2010). An Intelligent Internet Key Exchange Protocol Resistant to Denial-of-Service Attacks. 網際網路技術學刊. 11(5). 681–690. 1 indexed citations
12.
Su, Ming‐Yang. (2010). Internet worms identification through serial episodes mining. International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology. 132–136. 6 indexed citations
13.
Su, Ming‐Yang. (2010). Real-time anomaly detection systems for Denial-of-Service attacks by weighted k-nearest-neighbor classifiers. Expert Systems with Applications. 38(4). 3492–3498. 121 indexed citations
14.
Horng, Shi‐Jinn, et al.. (2008). Anomaly detection for web server based on smooth support vector machine.. Computer Systems: Science & Engineering. 23. 2 indexed citations
15.
Horng, Shi‐Jinn, et al.. (2006). A Surveillance Spyware Detection System Based on Data Mining Methods. 3236–3241. 24 indexed citations
16.
Chang, Cheng‐Hsien, et al.. (2003). Eyelid Tumors in Southern Taiwan: A 5‐Year Survey from a Medical University. The Kaohsiung Journal of Medical Sciences. 19(11). 549–553. 28 indexed citations
17.
Chen, Gen-Huey, et al.. (2001). A general broadcasting scheme for recursive networks with complete connection. Parallel Computing. 27(9). 1273–1278. 5 indexed citations
18.
Sheu, Jang‐Ping & Ming‐Yang Su. (1994). A MULTICAST ALGORITHM FOR HYPERCUBE MULTIPROCESSORS. Parallel algorithms and applications. 2(4). 277–290. 22 indexed citations
19.
Su, Ming‐Yang, et al.. (1982). Schwarz-Christoffel Theory of Flow Past an Opening. Journal of the Engineering Mechanics Division. 108(2). 399–418. 1 indexed citations
20.
Su, Ming‐Yang, et al.. (1973). An unsupervised classification technique for multispectral remote sensing data.. 3 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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