Jiaming Huang

450 total citations
14 papers, 291 citations indexed

About

Jiaming Huang is a scholar working on Artificial Intelligence, Information Systems and Statistical and Nonlinear Physics. According to data from OpenAlex, Jiaming Huang has authored 14 papers receiving a total of 291 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 8 papers in Information Systems and 7 papers in Statistical and Nonlinear Physics. Recurrent topics in Jiaming Huang's work include Spam and Phishing Detection (8 papers), Complex Network Analysis Techniques (7 papers) and Advanced Graph Neural Networks (7 papers). Jiaming Huang is often cited by papers focused on Spam and Phishing Detection (8 papers), Complex Network Analysis Techniques (7 papers) and Advanced Graph Neural Networks (7 papers). Jiaming Huang collaborates with scholars based in China, Australia and United States. Jiaming Huang's co-authors include Zhao Li, Jianliang Gao, Jian Yang, Jia Wu, Chuan Zhou, Haobo Wang, Zhiqiang Zhang, Yucong Duan, Yifan Yang and Bo An and has published in prestigious journals such as IEEE Access, Future Generation Computer Systems and ACM Transactions on Information Systems.

In The Last Decade

Jiaming Huang

13 papers receiving 280 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jiaming Huang China 10 218 107 64 54 32 14 291
Feifei Kou China 10 173 0.8× 76 0.7× 44 0.7× 17 0.3× 71 2.2× 31 262
Chun Jin China 5 300 1.4× 155 1.4× 55 0.9× 16 0.3× 21 0.7× 17 403
Jinghua Feng China 10 501 2.3× 207 1.9× 53 0.8× 71 1.3× 42 1.3× 13 575
Edward Benson United States 8 158 0.7× 149 1.4× 52 0.8× 87 1.6× 27 0.8× 16 316
Liang He China 9 159 0.7× 120 1.1× 102 1.6× 56 1.0× 34 1.1× 33 284
Gianni Costa Italy 12 210 1.0× 140 1.3× 69 1.1× 94 1.7× 32 1.0× 45 358
Guohui Ling China 6 243 1.1× 241 2.3× 92 1.4× 55 1.0× 53 1.7× 8 389
Yutaka Kidawara Japan 7 148 0.7× 91 0.9× 42 0.7× 48 0.9× 39 1.2× 45 248
Jeff Pasternack United States 7 279 1.3× 152 1.4× 39 0.6× 44 0.8× 20 0.6× 7 415

Countries citing papers authored by Jiaming Huang

Since Specialization
Citations

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

Fields of papers citing papers by Jiaming Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiaming Huang

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

All Works

14 of 14 papers shown
1.
Huang, Jiaming, et al.. (2025). CIRGNN: Leveraging Cross-Chart Relationships with a Graph Neural Network for Stock Price Prediction. Mathematics. 13(15). 2402–2402.
2.
Li, Zhao, Biao Wang, Jiaming Huang, et al.. (2023). A graph-powered large-scale fraud detection system. International Journal of Machine Learning and Cybernetics. 15(1). 115–128. 9 indexed citations
3.
Li, Zhao, Jiaming Huang, Jia Wu, et al.. (2022). eFraudCom: An E-commerce Fraud Detection System via Competitive Graph Neural Networks. ACM Transactions on Information Systems. 40(3). 1–29. 90 indexed citations
4.
Li, Zhao, Baokun Wang, Jia Wu, et al.. (2022). eRiskCom: an e-commerce risky community detection platform. The VLDB Journal. 31(5). 1085–1101. 18 indexed citations
5.
Huang, Jiaming, et al.. (2022). Research on fake reviews detection based on graph neural network. 24–24. 1 indexed citations
6.
Zhao, Li, Peng Zhang, Jiaming Huang, et al.. (2021). What Happens Behind the Scene? Towards Fraud Community Detection in E-Commerce from Online to Offline. 105–113. 17 indexed citations
7.
Li, Jingdong, Zhao Li, Jiaming Huang, et al.. (2021). Large-scale Fake Click Detection for E-commerce Recommendation Systems. 2595–2606. 9 indexed citations
8.
Li, Zhao, et al.. (2021). Live-Streaming Fraud Detection: A Heterogeneous Graph Neural Network Approach. 3670–3678. 25 indexed citations
9.
Li, Zhao, et al.. (2020). Large-scale online multi-view graph neural network and applications. Future Generation Computer Systems. 116. 145–155. 20 indexed citations
10.
Wang, Haobo, Zhao Li, Jiaming Huang, et al.. (2020). Collaboration Based Multi-Label Propagation for Fraud Detection. 2477–2483. 22 indexed citations
11.
Li, Zhao, Jialin Wang, Jiaming Huang, et al.. (2020). Category-aware Graph Neural Networks for Improving E-commerce Review Helpfulness Prediction. 2693–2700. 15 indexed citations
12.
Li, Zhao, et al.. (2019). MV-GCN: Multi-View Graph Convolutional Networks for Link Prediction. IEEE Access. 7. 176317–176328. 33 indexed citations
13.
Guo, Qingyu, Zhao Li, Bo An, et al.. (2019). Securing the Deep Fraud Detector in Large-Scale E-Commerce Platform via Adversarial Machine Learning Approach. 616–626. 28 indexed citations
14.
Huang, Jiaming, et al.. (2018). Unsupervised Multi-view Nonlinear Graph Embedding. Uncertainty in Artificial Intelligence. 319–328. 4 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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2026