Zhonghai Wu

2.1k total citations
161 papers, 1.1k citations indexed

About

Zhonghai Wu is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Zhonghai Wu has authored 161 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 84 papers in Artificial Intelligence, 79 papers in Information Systems and 52 papers in Computer Networks and Communications. Recurrent topics in Zhonghai Wu's work include Cloud Data Security Solutions (24 papers), Software System Performance and Reliability (22 papers) and Cloud Computing and Resource Management (22 papers). Zhonghai Wu is often cited by papers focused on Cloud Data Security Solutions (24 papers), Software System Performance and Reliability (22 papers) and Cloud Computing and Resource Management (22 papers). Zhonghai Wu collaborates with scholars based in China, United States and Singapore. Zhonghai Wu's co-authors include Hongzhi Liu, Qingni Shen, Ying Li, Ying Li, D. Frank Hsu, Xing Zhang, Chao‐Hsien Chu, Yang Zhou, Dawei Zhang and Bin Fu and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and ACM Computing Surveys.

In The Last Decade

Zhonghai Wu

146 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhonghai Wu China 15 690 457 299 162 91 161 1.1k
Gansen Zhao China 19 439 0.6× 513 1.1× 303 1.0× 152 0.9× 86 0.9× 111 1.1k
Yafeng Ren China 25 1.5k 2.1× 450 1.0× 104 0.3× 82 0.5× 114 1.3× 69 1.8k
Sanjay Kumar India 21 600 0.9× 191 0.4× 230 0.8× 183 1.1× 159 1.7× 100 1.3k
Bofeng Zhang China 15 358 0.5× 497 1.1× 353 1.2× 188 1.2× 54 0.6× 160 1.1k
K. G. Srinivasa India 15 356 0.5× 228 0.5× 128 0.4× 114 0.7× 78 0.9× 129 821
Pengfei Liu China 23 2.0k 2.8× 236 0.5× 51 0.2× 316 2.0× 132 1.5× 80 2.3k
Xiaomei Yu China 16 600 0.9× 378 0.8× 199 0.7× 259 1.6× 109 1.2× 66 1.1k
Andrew O. Arnold United States 12 985 1.4× 205 0.4× 384 1.3× 203 1.3× 222 2.4× 23 1.3k
Zhu Sun Singapore 17 640 0.9× 836 1.8× 104 0.3× 186 1.1× 74 0.8× 79 1.3k
Jilian Zhang China 17 794 1.2× 268 0.6× 110 0.4× 333 2.1× 114 1.3× 42 1.2k

Countries citing papers authored by Zhonghai Wu

Since Specialization
Citations

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

Fields of papers citing papers by Zhonghai Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhonghai Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Zhonghai Wu. A scholar is included among the top collaborators of Zhonghai Wu 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 Zhonghai Wu. Zhonghai Wu 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.
Shen, Qingni, et al.. (2025). Redactable Blockchain From Decentralized Chameleon Hash Functions, Revisited. IEEE Transactions on Computers. 74(6). 1911–1920.
2.
Liu, Hongzhi, et al.. (2025). Quasi-Metric Learning for Bilateral Person-Job Fit. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(5). 3947–3960. 1 indexed citations
3.
Tan, Xiaoli, et al.. (2025). E-Log: Fine-Grained Elastic Log-Based Anomaly Detection and Diagnosis for Databases. IEEE Transactions on Services Computing. 18(5). 2808–2821. 1 indexed citations
4.
Jia, Mengxi, Yifan Wu, Aiwei Liu, et al.. (2025). A Survey of AIOps in the Era of Large Language Models. ACM Computing Surveys. 58(2). 1–35. 2 indexed citations
5.
Jia, Mengxi, et al.. (2024). Multivariate Log-based Anomaly Detection for Distributed Database. arXiv (Cornell University). 4256–4267. 5 indexed citations
6.
Zhang, Shikun, et al.. (2024). SWAT4J: Generating System Call Allowlist for Java Container Attack Surface Reduction. 929–939. 2 indexed citations
7.
Zhang, Zhi, et al.. (2024). ThermalScope: A Practical Interrupt Side Channel Attack Based on Thermal Event Interrupts. UWA Profiles and Research Repository (UWA). 1–6. 1 indexed citations
8.
Liu, Hongzhi, et al.. (2024). Adaptive Ensemble Learning With Category-Aware Attention and Local Contrastive Loss. IEEE Transactions on Circuits and Systems for Video Technology. 35(2). 1224–1236.
9.
Huang, Xiaosong, et al.. (2024). UAC-AD: Unsupervised Adversarial Contrastive Learning for Anomaly Detection on Multi-Modal Data in Microservice Systems. IEEE Transactions on Services Computing. 17(6). 3887–3900. 5 indexed citations
10.
Jia, Mengxi, et al.. (2024). Towards Close-to-Zero Runtime Collection Overhead: Raft-Based Anomaly Diagnosis on System Faults for Distributed Storage System. IEEE Transactions on Services Computing. 18(2). 1054–1067. 4 indexed citations
11.
Shen, Qingni, et al.. (2024). ReenRepair: Automatic and semantic equivalent repair of reentrancy in smart contracts. Journal of Systems and Software. 216. 112107–112107. 2 indexed citations
12.
Feng, Xinyu, Qingni Shen, Cong Li, Yuejian Fang, & Zhonghai Wu. (2024). Privacy Preserving Federated Learning from Multi-Input Functional Proxy Re-Encryption. 6955–6959. 1 indexed citations
13.
Xie, Yutao, et al.. (2023). Survey of Code Search Based on Deep Learning. ACM Transactions on Software Engineering and Methodology. 33(2). 1–42. 11 indexed citations
14.
Xia, Wen‐Sheng, Ying Li, Lan Zhang, Zhonghai Wu, & Xiaoyong Yuan. (2023). Cascade Vertical Federated Learning Towards Straggler Mitigation and Label Privacy Over Distributed Labels. IEEE Transactions on Big Data. 10(6). 926–939. 5 indexed citations
15.
Liu, Hongzhi, et al.. (2023). Knowledge Graph-Based Behavior Denoising and Preference Learning for Sequential Recommendation. IEEE Transactions on Knowledge and Data Engineering. 36(6). 2490–2503. 6 indexed citations
16.
Shen, Qingni, et al.. (2022). T-Counter: Trustworthy and Efficient CPU Resource Measurement Using SGX in the Cloud. IEEE Transactions on Dependable and Secure Computing. 20(1). 867–885. 5 indexed citations
17.
Liu, Hongzhi, et al.. (2019). Representation Learning with Ordered Relation Paths for Knowledge Graph Completion. 2662–2671. 12 indexed citations
18.
Wu, Zhonghai. (2012). A Micro Blog User Community Aware Method Based on Hypergraph. Xi'an Jiaotong Daxue xuebao. 2 indexed citations
19.
Zheng, Mianping, et al.. (2010). U-Th Isochron Dating of Impure Carbonates and the Possible Effect of Isotopic Fractionation during Leaching. Acta Geological Sinica. 84(8). 1146–1154. 8 indexed citations
20.
Liu, Hongzhi, et al.. (2009). Efficient improvement for adaboost based face detection system. e+i Elektrotechnik und Informationstechnik. 2. 1453–1457. 1 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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