Jiale Guo

434 total citations
17 papers, 241 citations indexed

About

Jiale Guo is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Jiale Guo has authored 17 papers receiving a total of 241 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 4 papers in Information Systems and 3 papers in Computer Networks and Communications. Recurrent topics in Jiale Guo's work include Privacy-Preserving Technologies in Data (7 papers), Cryptography and Data Security (4 papers) and Advanced Graph Neural Networks (3 papers). Jiale Guo is often cited by papers focused on Privacy-Preserving Technologies in Data (7 papers), Cryptography and Data Security (4 papers) and Advanced Graph Neural Networks (3 papers). Jiale Guo collaborates with scholars based in China, Singapore and Australia. Jiale Guo's co-authors include Kwok‐Yan Lam, Ziyao Liu, Jun Zhao, Wenzhuo Yang, Bowen Shen, Li Wang, Ting Wang, Feng Li, Guiyi Wei and Qing Zhang and has published in prestigious journals such as IEEE Access, IEEE Transactions on Vehicular Technology and IEEE Internet of Things Journal.

In The Last Decade

Jiale Guo

16 papers receiving 237 citations

Peers

Jiale Guo
Peng Tang China
Virat Shejwalkar United States
Minghong Fang United States
Jiale Guo
Citations per year, relative to Jiale Guo Jiale Guo (= 1×) peers Yuanqin He

Countries citing papers authored by Jiale Guo

Since Specialization
Citations

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

Fields of papers citing papers by Jiale Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiale Guo

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

All Works

17 of 17 papers shown
1.
Liu, Ziyao, et al.. (2025). Privacy-Preserving Federated Unlearning With Certified Client Removal. IEEE Transactions on Information Forensics and Security. 20. 3966–3978. 2 indexed citations
2.
Guo, Jiale, et al.. (2024). Machine learning-based prediction of vitamin D deficiency: NHANES 2001-2018. Frontiers in Endocrinology. 15. 1327058–1327058. 12 indexed citations
4.
Liu, Ziyao, et al.. (2024). Dynamic User Clustering for Efficient and Privacy-Preserving Federated Learning. IEEE Transactions on Dependable and Secure Computing. 1–12. 9 indexed citations
5.
Liu, Ziyao, et al.. (2023). Privacy-Enhanced Knowledge Transfer with Collaborative Split Learning over Teacher Ensembles. DR-NTU (Nanyang Technological University). 1–13. 4 indexed citations
7.
Xu, Minrui, Jiale Guo, Lwin Khin Shar, et al.. (2023). Decentralized Multimedia Data Sharing in IoV: A Learning-Based Equilibrium of Supply and Demand. IEEE Transactions on Vehicular Technology. 73(3). 4035–4050. 6 indexed citations
8.
Guo, Jiale, et al.. (2023). Blockchain-Based Privacy-Preserving Federated Learning for Mobile Crowdsourcing. IEEE Internet of Things Journal. 11(8). 13884–13899. 6 indexed citations
9.
Wang, Ting, et al.. (2022). A Knowledge Graph-Gcn-Community Detection Integrated Model for Large-Scale Stock Price Prediction. SSRN Electronic Journal. 1 indexed citations
10.
Liu, Ziyao, Jiale Guo, Kwok‐Yan Lam, & Jun Zhao. (2022). Efficient Dropout-Resilient Aggregation for Privacy-Preserving Machine Learning. IEEE Transactions on Information Forensics and Security. 18. 1839–1854. 72 indexed citations
11.
Liu, Ziyao, et al.. (2022). Privacy-Preserving Aggregation in Federated Learning: A Survey. IEEE Transactions on Big Data. 1–20. 69 indexed citations
12.
Li, Feng, Bowen Shen, Jiale Guo, et al.. (2022). Dynamic Spectrum Access for Internet-of-Things Based on Federated Deep Reinforcement Learning. IEEE Transactions on Vehicular Technology. 71(7). 7952–7956. 26 indexed citations
13.
Wang, Ting, et al.. (2021). IFTA: Iterative filtering by using TF-AICL algorithm for Chinese encyclopedia knowledge refinement. Applied Intelligence. 51(8). 6265–6293. 7 indexed citations
14.
Ye, Rui, et al.. (2021). Dynamic Graph Construction for Improving Diversity of Recommendation. 651–655. 17 indexed citations
15.
Wang, Ting, Jie Li, & Jiale Guo. (2021). A scalable parallel Chinese online encyclopedia knowledge denoising method based on entry tags and Spark cluster. Applied Intelligence. 51(10). 7573–7599. 4 indexed citations
16.
Wang, Ting, et al.. (2019). A Novel Large-scale Chinese Encyclopedia Knowledge Parallel Refining Method Based on MapReduce. IEEE Access. 7. 111840–111857. 1 indexed citations
17.
Nguyen, Minh Nhut, Jiale Guo, & Daming Shi. (2006). ESOFCMAC: Evolving Self-Organizing Fuzzy Cerebellar Model Articulation Controller. The 2006 IEEE International Joint Conference on Neural Network Proceedings. 5. 3694–3699. 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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