Leijie Wu

521 total citations · 1 hit paper
13 papers, 374 citations indexed

About

Leijie Wu is a scholar working on Artificial Intelligence, Computer Science Applications and Computer Networks and Communications. According to data from OpenAlex, Leijie Wu has authored 13 papers receiving a total of 374 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 5 papers in Computer Science Applications and 2 papers in Computer Networks and Communications. Recurrent topics in Leijie Wu's work include Privacy-Preserving Technologies in Data (9 papers), Mobile Crowdsensing and Crowdsourcing (5 papers) and Cryptography and Data Security (3 papers). Leijie Wu is often cited by papers focused on Privacy-Preserving Technologies in Data (9 papers), Mobile Crowdsensing and Crowdsourcing (5 papers) and Cryptography and Data Security (3 papers). Leijie Wu collaborates with scholars based in Hong Kong, China and Japan. Leijie Wu's co-authors include Song Guo, Zicong Hong, Yufeng Zhan, Peng Li, Jie Zhang, Huarong Nie, Aihua He, Xiao Han, Junxiao Wang and Wenchao Xu and has published in prestigious journals such as ACS Applied Materials & Interfaces, Carcinogenesis and IEEE Transactions on Computers.

In The Last Decade

Leijie Wu

13 papers receiving 366 citations

Hit Papers

A Survey of Incentive Mechanism Design for Federated Lear... 2021 2026 2022 2024 2021 50 100 150

Peers

Leijie Wu
Renato R. Maaliw Philippines
Maryam Zaffar Pakistan
Zhuojun Duan United States
Lassaad K. Smirani Saudi Arabia
Leijie Wu
Citations per year, relative to Leijie Wu Leijie Wu (= 1×) peers Juntao Tan

Countries citing papers authored by Leijie Wu

Since Specialization
Citations

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

Fields of papers citing papers by Leijie Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Leijie Wu

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

All Works

13 of 13 papers shown
1.
Wu, Leijie, et al.. (2024). Rethinking Personalized Client Collaboration in Federated Learning. IEEE Transactions on Mobile Computing. 23(12). 11227–11239. 6 indexed citations
2.
Guo, Song, et al.. (2024). Chiron: A Robustness-Aware Incentive Scheme for Edge Learning via Hierarchical Reinforcement Learning. IEEE Transactions on Mobile Computing. 23(8). 8508–8524. 2 indexed citations
3.
Guo, Song, et al.. (2024). QuickDrop: Efficient Federated Unlearning via Synthetic Data Generation. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 266–278. 3 indexed citations
4.
Wu, Leijie, et al.. (2023). Long-Term Adaptive VCG Auction Mechanism for Sustainable Federated Learning With Periodical Client Shifting. IEEE Transactions on Mobile Computing. 23(5). 6060–6073. 12 indexed citations
5.
Wu, Leijie, Isamu Saito, Kenta Hongo, & Kosuke Okeyoshi. (2023). Recognition of Spatial Finiteness in Meniscus Splitting Based on Evaporative Interface Fluctuations. Advanced Materials Interfaces. 10(34). 3 indexed citations
6.
Saito, Isamu, Leijie Wu, Mitsuo Hara, et al.. (2022). Anisotropic Responses with Cation Selectivity in Hierarchically Ordered Polysaccharide Networks. ACS Applied Polymer Materials. 4(10). 7054–7060. 4 indexed citations
7.
Wu, Leijie, et al.. (2022). Federated Unlearning: Guarantee the Right of Clients to Forget. IEEE Network. 36(5). 129–135. 30 indexed citations
8.
Wu, Leijie, et al.. (2022). Sustainable Federated Learning with Long-term Online VCG Auction Mechanism. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 895–905. 5 indexed citations
9.
Zhan, Yufeng, Jie Zhang, Zicong Hong, et al.. (2021). A Survey of Incentive Mechanism Design for Federated Learning. IEEE Transactions on Emerging Topics in Computing. 1–1. 198 indexed citations breakdown →
10.
Zhan, Yufeng, Peng Li, Leijie Wu, & Song Guo. (2021). L4L: Experience-Driven Computational Resource Control in Federated Learning. IEEE Transactions on Computers. 71(4). 971–983. 26 indexed citations
11.
Wu, Leijie, et al.. (2021). Incentive-Driven Long-term Optimization for Edge Learning by Hierarchical Reinforcement Mechanism. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 35–45. 9 indexed citations
12.
Han, Xiao, et al.. (2019). Inorganic–Organic Hybrid Janus Fillers for Improving the Thermal Conductivity of Polymer Composites. ACS Applied Materials & Interfaces. 11(13). 12190–12194. 40 indexed citations
13.
Zhu, Xiao, Jinfang Zhang, Wenguo Fan, et al.. (2013). The rs391957 variant cis-regulating oncogene GRP78 expression contributes to the risk of hepatocellular carcinoma. Carcinogenesis. 34(6). 1273–1280. 36 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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