Hang Liu

545 total citations
28 papers, 374 citations indexed

About

Hang Liu is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Hang Liu has authored 28 papers receiving a total of 374 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Artificial Intelligence, 10 papers in Electrical and Electronic Engineering and 9 papers in Computer Vision and Pattern Recognition. Recurrent topics in Hang Liu's work include Privacy-Preserving Technologies in Data (12 papers), Stochastic Gradient Optimization Techniques (9 papers) and Advanced Graph Neural Networks (6 papers). Hang Liu is often cited by papers focused on Privacy-Preserving Technologies in Data (12 papers), Stochastic Gradient Optimization Techniques (9 papers) and Advanced Graph Neural Networks (6 papers). Hang Liu collaborates with scholars based in United States, Hong Kong and China. Hang Liu's co-authors include Ying–Jun Angela Zhang, Xiaojun Yuan, Zehong Lin, Fan Yao, Caiwen Ding, Abdulrahman Alhothaily, Chunqiang Hu, Arwa Alrawais, Xiuzhen Cheng and Jinbo Bi and has published in prestigious journals such as IEEE Transactions on Signal Processing, Optics Express and IEEE Transactions on Communications.

In The Last Decade

Hang Liu

24 papers receiving 369 citations

Peers

Hang Liu
Xin Fan China
Hang Qi China
Reem Melki Lebanon
Xinsheng Ji China
Guanbo Zheng United States
Pieter Robyns Belgium
Pinchang Zhang China
Christian Zenger Germany
Adam C. Polak United States
Heinrich Luecken Switzerland
Xin Fan China
Hang Liu
Citations per year, relative to Hang Liu Hang Liu (= 1×) peers Xin Fan

Countries citing papers authored by Hang Liu

Since Specialization
Citations

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

Fields of papers citing papers by Hang Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hang Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Hang Liu. A scholar is included among the top collaborators of Hang Liu 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 Hang Liu. Hang Liu 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.
Liu, Yuan, et al.. (2025). A Two-Timescale Approach for Wireless Federated Learning With Parameter Freezing and Power Control. IEEE Transactions on Mobile Computing. 24(9). 8841–8855.
2.
Liu, Yuan, et al.. (2024). Two-Timescale Energy Optimization for Wireless Federated Learning. 1–6. 2 indexed citations
3.
Campbell, Andrew R., Hang Liu, Anna Scaglione, & Tong Wu. (2024). A Federated Learning Approach for Graph Convolutional Neural Networks. 34. 1–5. 1 indexed citations
4.
Liu, Hang, Anna Scaglione, & Sean Peisert. (2024). Privacy Leakage In Graph Signal To Graph Matching Problems. eScholarship (California Digital Library). 9371–9375.
5.
Liu, Hang, Yan Jia, & Ying–Jun Angela Zhang. (2024). Differentially Private Over-the-Air Federated Learning Over MIMO Fading Channels. IEEE Transactions on Wireless Communications. 23(8). 8232–8247. 4 indexed citations
6.
Liu, Hang, Anna Scaglione, & Hoi-To Wai. (2023). Solutions of the Graph Matching Problem Using Graph Signals. 119. 266–270. 2 indexed citations
7.
Liu, Hang, Yan Jia, & Ying–Jun Angela Zhang. (2023). On the Privacy Leakage of Over-the-Air Federated Learning Over MIMO Fading Channels. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 1 indexed citations
8.
Lin, Zehong, Hang Liu, & Ying–Jun Angela Zhang. (2023). CFLIT: Coexisting Federated Learning and Information Transfer. IEEE Transactions on Wireless Communications. 22(11). 8436–8453. 7 indexed citations
9.
Wang, Yijue, Chenghong Wang, Hang Liu, et al.. (2022). Variance of the Gradient Also Matters: Privacy Leakage from Gradients. 2022 International Joint Conference on Neural Networks (IJCNN). 1–8. 2 indexed citations
10.
Song, Shuaiwen Leon, Yongchao Liu, Heng Zhang, et al.. (2022). T-GCN. 69–82. 5 indexed citations
11.
Liu, Hang, Xiaojun Yuan, & Ying–Jun Angela Zhang. (2021). CSIT-Free Model Aggregation for Federated Edge Learning via Reconfigurable Intelligent Surface. IEEE Wireless Communications Letters. 10(11). 2440–2444. 13 indexed citations
12.
Chen, Shiyang, Santosh Pandey, Bingbing Li, et al.. (2021). E.T.. 1–18. 10 indexed citations
13.
Liu, Jiawen, et al.. (2021). Tahoe. 426–440. 13 indexed citations
14.
Shi, Runbin, et al.. (2020). FTDL: An FPGA-tailored Architecture for Deep Learning Systems. 320–320. 3 indexed citations
15.
Kuai, Xiaoyan, Xiaojun Yuan, Wenjing Yan, Hang Liu, & Ying–Jun Angela Zhang. (2020). Double-Sparsity Learning-Based Channel-and-Signal Estimation in Massive MIMO With Generalized Spatial Modulation. IEEE Transactions on Communications. 68(5). 2863–2877. 17 indexed citations
16.
Liu, Hang, Zhen−Qiang Yin, Rong Wang, et al.. (2020). Finite-key analysis for round-robin-differential-phase-shift quantum key distribution. Optics Express. 28(10). 15416–15416. 1 indexed citations
17.
18.
Wang, Yijue, Chenghong Wang, Zigeng Wang, et al.. (2020). MCMIA: Model Compression Against Membership Inference Attack in Deep Neural Networks.. 5 indexed citations
19.
Liu, Hang, Xiaojun Yuan, & Ying–Jun Angela Zhang. (2019). Super-Resolution Blind Channel-and-Signal Estimation for Massive MIMO With One-Dimensional Antenna Array. IEEE Transactions on Signal Processing. 67(17). 4433–4448. 26 indexed citations
20.
Li, Meifeng, Guanzhong Dai, Hang Liu, & Wei Hu. (2007). Design of an Instruction for Fast and Efficient S-Box Implementation. 623–626. 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Xin Fan Breakdown of academic impact, for papers by Hang Qi Breakdown of academic impact, for papers by Reem Melki Breakdown of academic impact, for papers by Xinsheng Ji Breakdown of academic impact, for papers by Guanbo Zheng Breakdown of academic impact, for papers by Pieter Robyns Breakdown of academic impact, for papers by Pinchang Zhang Breakdown of academic impact, for papers by Christian Zenger Breakdown of academic impact, for papers by Adam C. Polak Breakdown of academic impact, for papers by Heinrich Luecken
Rankless by CCL
2026