Zeyi Tao

692 total citations
17 papers, 471 citations indexed

About

Zeyi Tao is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Plant Science. According to data from OpenAlex, Zeyi Tao has authored 17 papers receiving a total of 471 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 2 papers in Plant Science. Recurrent topics in Zeyi Tao's work include Privacy-Preserving Technologies in Data (5 papers), Stochastic Gradient Optimization Techniques (5 papers) and Advanced Neural Network Applications (4 papers). Zeyi Tao is often cited by papers focused on Privacy-Preserving Technologies in Data (5 papers), Stochastic Gradient Optimization Techniques (5 papers) and Advanced Neural Network Applications (4 papers). Zeyi Tao collaborates with scholars based in United States and China. Zeyi Tao's co-authors include Qun Li, Qi Xia, Zijiang Hao, Shanhe Yi, Cheng Li, Zenghong Ma, Xiaoqiang Du, Songqing Chen, Sheng Zhong and Chuanyu Wu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Proceedings of the IEEE and Biosystems Engineering.

In The Last Decade

Zeyi Tao

16 papers receiving 457 citations

Peers

Zeyi Tao

AI

CNC

IS

EEE

CVPR

Rohit Raja India

Chunlai Du China

Juhi Gupta India

Hany Harb Egypt

Javed Ferzund Pakistan

Nitin Rakesh India

Urmish Thakker United States

Bong Jun Ko United States

Jani Suomalainen Finland

Mohammed Q. Shatnawi Jordan

Rohit Raja India

Zeyi Tao

169 ×0.6

AI

218 ×1.1

CNC

59 ×0.6

IS

40 ×0.5

EEE

138 ×2.2

CVPR

Citations per year, relative to Zeyi Tao Zeyi Tao (= 1×) peers Rohit Raja

Countries citing papers authored by Zeyi Tao

Since Specialization

Citations

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

Fields of papers citing papers by Zeyi Tao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zeyi Tao

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

All Works

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17 of 17 papers shown

1.

Xia, Qi, Zeyi Tao, Qun Li, & Songqing Chen. (2023). Byzantine Tolerant Algorithms for Federated Learning. IEEE Transactions on Network Science and Engineering. 1–13. 8 indexed citations

2.

Tao, Zeyi, et al.. (2023). LAWS: Look Around and Warm-Start Natural Gradient Descent for Quantum Neural Networks. 76–82. 1 indexed citations

3.

Tao, Zeyi, Qi Xia, Songqing Chen, & Qun Li. (2022). An Efficient and Robust Cloud-Based Deep Learning With Knowledge Distillation. IEEE Transactions on Cloud Computing. 11(2). 1733–1745. 12 indexed citations

4.

Tao, Zeyi, et al.. (2022). Privacy-Preserving and Robust Federated Deep Metric Learning. 1–11.

5.

Tao, Zeyi, et al.. (2022). wpScalable Quantum Neural Networks for Classification. 38–48. 14 indexed citations

6.

Xia, Qi, et al.. (2021). A survey of federated learning for edge computing: Research problems and solutions. SHILAP Revista de lepidopterología. 1(1). 100008–100008. 179 indexed citations

7.

Xia, Qi, Zeyi Tao, & Qun Li. (2021). Defending Against Byzantine Attacks in Quantum Federated Learning. 145–152. 14 indexed citations

8.

Tao, Zeyi, Qi Xia, & Qun Li. (2021). Neuron Manifold Distillation for Edge Deep Learning. 1–10. 2 indexed citations

9.

Ma, Zenghong, et al.. (2021). Automatic detection of crop root rows in paddy fields based on straight-line clustering algorithm and supervised learning method. Biosystems Engineering. 211. 63–76. 34 indexed citations

10.

Tao, Zeyi, et al.. (2021). CE-SGD: Communication-Efficient Distributed Machine Learning. 2021 IEEE Global Communications Conference (GLOBECOM). 1–7. 2 indexed citations

11.

Cheng, Yin, Zenghong Ma, Zeyi Tao, Xiaoqiang Du, & Guofeng Zhang. (2021). Acquiring navigation deviation in farmland by fusing satellite and visual information. 1 indexed citations

12.

Tao, Zeyi, et al.. (2020). <i>A crop root row detection algorithm for visual navigation in rice fields</i>. 1 indexed citations

13.

Xia, Qi, Zeyi Tao, & Qun Li. (2020). Defenses Against Byzantine Attacks in Distributed Deep Neural Networks. IEEE Transactions on Network Science and Engineering. 8(3). 2025–2035. 12 indexed citations

14.

Tao, Zeyi, Qi Xia, Zijiang Hao, et al.. (2019). A Survey of Virtual Machine Management in Edge Computing. Proceedings of the IEEE. 107(8). 1482–1499. 88 indexed citations

15.

Xia, Qi, Zeyi Tao, Zijiang Hao, & Qun Li. (2019). FABA: An Algorithm for Fast Aggregation against Byzantine Attacks in Distributed Neural Networks. 4824–4830. 53 indexed citations

16.

Tao, Zeyi, Qi Xia, & Qun Li. (2019). A new perspective in understanding of Adam-Type algorithms and beyond. 1 indexed citations

17.

Tao, Zeyi & Qun Li. (2018). eSGD: Communication Efficient Distributed Deep Learning on the Edge. 49 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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