Bingzhe Wu

1.2k total citations
33 papers, 455 citations indexed

About

Bingzhe Wu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Bingzhe Wu has authored 33 papers receiving a total of 455 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 6 papers in Information Systems. Recurrent topics in Bingzhe Wu's work include Privacy-Preserving Technologies in Data (9 papers), Adversarial Robustness in Machine Learning (5 papers) and Topic Modeling (4 papers). Bingzhe Wu is often cited by papers focused on Privacy-Preserving Technologies in Data (9 papers), Adversarial Robustness in Machine Learning (5 papers) and Topic Modeling (4 papers). Bingzhe Wu collaborates with scholars based in China, United States and Hong Kong. Bingzhe Wu's co-authors include Chaochao Chen, Li Wang, Xiaolin Zheng, Yan Yan, Zhihang Yuan, Jun Zhou, Size Zheng, Guangyu Sun, Xuehai Qian and Yun Liang and has published in prestigious journals such as Nature Methods, IEEE Transactions on Neural Networks and Learning Systems and The International Journal of Advanced Manufacturing Technology.

In The Last Decade

Bingzhe Wu

32 papers receiving 443 citations

Peers

Bingzhe Wu

CVPR

EEE

CNC

Matej Balog United Kingdom

Amit Agarwal India

Alexander Novikov Russia

Lei Fang China

Alhussein Fawzi United Kingdom

Qiang Zeng United States

Xiaozhang Liu China

Mahmudur Rahman United States

Somanath Tripathy India

Rex Ying United States

Matej Balog United Kingdom

Bingzhe Wu

218 ×0.8

44 ×0.6

CVPR

86 ×1.3

47 ×0.9

EEE

45 ×0.9

CNC

Citations per year, relative to Bingzhe Wu Bingzhe Wu (= 1×) peers Matej Balog

Countries citing papers authored by Bingzhe Wu

Since Specialization

Citations

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

Fields of papers citing papers by Bingzhe Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bingzhe Wu

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

All Works

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20 of 20 papers shown

Hu, Zhanyi, et al.. (2025). A Review and Experimental Evaluation on Split Learning. Future Internet. 17(2). 87–87. 3 indexed citations

Wu, Bingzhe, et al.. (2025). AuditAgent: Expert-Guided Multi-Agent Reasoning for Cross-Document Fraudulent Evidence Discovery. 1–9.

Zhao, Yu, Bing He, Zongbo Han, et al.. (2024). Learning With Noisy Labels Over Imbalanced Subpopulations. IEEE Transactions on Neural Networks and Learning Systems. 36(4). 6544–6555. 7 indexed citations

Li, Wei, Fan Yang, Fang Wang, et al.. (2024). scPROTEIN: a versatile deep graph contrastive learning framework for single-cell proteomics embedding. Nature Methods. 21(4). 623–634. 16 indexed citations

Chen, Liang, et al.. (2024). Rethinking and Simplifying Bootstrapped Graph Latents. 665–673. 2 indexed citations

Bian, Yatao, et al.. (2024). Variate Associated Domain Adaptation for Unsupervised Multivariate Time Series Anomaly Detection. ACM Transactions on Knowledge Discovery from Data. 18(8). 1–24. 4 indexed citations

Liang, Chen, et al.. (2023). Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 6325–6341. 6 indexed citations

Yuan, Zhihang, et al.. (2023). Post-Training Quantization on Diffusion Models. 1972–1981. 52 indexed citations

Cao, Zeyu, Zhipeng Liang, Bingzhe Wu, et al.. (2023). Privacy Matters: Vertical Federated Linear Contextual Bandits for Privacy Protected Recommendation. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 154–166. 3 indexed citations

10.

Ji, Yuanfeng, Lu Zhang, Jiaxiang Wu, et al.. (2023). DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery – a Focus on Affinity Prediction Problems with Noise Annotations. Proceedings of the AAAI Conference on Artificial Intelligence. 37(7). 8023–8031. 19 indexed citations

11.

Zhang, Zhen, Mengting Hu, Shiwan Zhao, et al.. (2023). E-NER: Evidential Deep Learning for Trustworthy Named Entity Recognition. 1619–1634. 7 indexed citations

12.

Yang, Tao, et al.. (2023). PsyCoT: Psychological Questionnaire as Powerful Chain-of-Thought for Personality Detection. 3305–3320. 7 indexed citations

13.

Wu, Bingzhe, et al.. (2023). COPPER: a combinatorial optimization problem solver with processing-in-memory architecture. Frontiers of Information Technology & Electronic Engineering. 24(5). 731–741. 2 indexed citations

14.

Han, Zhaoyang, Chunpeng Ge, Bingzhe Wu, & Zhe Liu. (2022). Lightweight Privacy-Preserving Federated Incremental Decision Trees. IEEE Transactions on Services Computing. 1–13. 6 indexed citations

15.

Zhou, Jun, Chaochao Chen, Yan Wang, et al.. (2022). Toward Scalable and Privacy-preserving Deep Neural Network via Algorithmic-Cryptographic Co-design. ACM Transactions on Intelligent Systems and Technology. 13(4). 1–21. 2 indexed citations

16.

Chen, Chaochao, Jun Zhou, Huiwen Wu, et al.. (2022). Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. 1959–1965. 41 indexed citations

17.

Zhou, Jun, et al.. (2021). ASFGNN: Automated separated-federated graph neural network. Peer-to-Peer Networking and Applications. 14(3). 1692–1704. 46 indexed citations

18.

Yuan, Zhihang, et al.. (2021). NAS4RRAM: neural network architecture search for inference on RRAM-based accelerators. Science China Information Sciences. 64(6). 24 indexed citations

19.

Chen, Chaochao, Jun Zhou, Bingzhe Wu, et al.. (2020). Practical Privacy Preserving POI Recommendation. ACM Transactions on Intelligent Systems and Technology. 11(5). 1–20. 53 indexed citations

20.

Wu, Bingzhe, Shiwan Zhao, Chaochao Chen, et al.. (2019). Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection. Neural Information Processing Systems. 32. 306–316. 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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