Zekun Shi

447 total citations · 1 hit paper
7 papers, 176 citations indexed

About

Zekun Shi is a scholar working on Artificial Intelligence, Building and Construction and Food Science. According to data from OpenAlex, Zekun Shi has authored 7 papers receiving a total of 176 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 1 paper in Building and Construction and 1 paper in Food Science. Recurrent topics in Zekun Shi's work include Privacy-Preserving Technologies in Data (3 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Refrigeration and Air Conditioning Technologies (1 paper). Zekun Shi is often cited by papers focused on Privacy-Preserving Technologies in Data (3 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Refrigeration and Air Conditioning Technologies (1 paper). Zekun Shi collaborates with scholars based in China, Japan and Hong Kong. Zekun Shi's co-authors include Mang Ye, Bo Du, Wenke Huang, Li He, Qiang Yang, Junhong Yang, Bo Du, Zhuang Li, Jianghua Zheng and Li He and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Information Forensics and Security and International Journal of Refrigeration.

In The Last Decade

Zekun Shi

6 papers receiving 176 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Federated Learning for Generalization, Robustness, Fairness: A Survey and Benchmark

2024 56 citations Wenke Huang, Mang Ye et al. IEEE Transactions on Pattern Analysis and Machine Intelligence profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Zekun Shi China	4	128	24	15	13	12	7	176
Zain Ul Abideen Pakistan	8	61 0.5×	27 1.1×	12 0.8×	8 0.6×	24 2.0×	22	155
Lambodar Jena India	7	46 0.4×	28 1.2×	18 1.2×	17 1.3×	19 1.6×	17	147
Fengda Zhang China	5	99 0.8×	31 1.3×	17 1.1×	46 3.5×	36 3.0×	22	183
Ayush K Tarun India	4	108 0.8×	38 1.6×	12 0.8×	16 1.2×	17 1.4×	6	178
Raj Kumar Patra India	7	73 0.6×	27 1.1×	17 1.1×	12 0.9×	21 1.8×	30	171
Nishant Kumar India	4	154 1.2×	17 0.7×	16 1.1×	10 0.8×	26 2.2×	8	184
Jindong Gu United Kingdom	7	149 1.2×	78 3.3×	11 0.7×	13 1.0×	11 0.9×	32	217
Leonard Lausen United States	3	61 0.5×	50 2.1×	9 0.6×	8 0.6×	7 0.6×	5	127
Jianyu Wang United States	6	138 1.1×	15 0.6×	23 1.5×	40 3.1×	27 2.3×	10	171

Countries citing papers authored by Zekun Shi

Since Specialization

Citations

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

Fields of papers citing papers by Zekun Shi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zekun Shi

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

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Huang, Wenke, Mang Ye, Zekun Shi, Li He, & Bo Du. (2025). Kindle Federated Generalization With Domain Specialized and Invariant Knowledge. IEEE Transactions on Information Forensics and Security. 20. 3461–3474.

2.

Huang, Xiaolin, et al.. (2025). Process optimization and flavor characteristics of cream cheese fermented with avocado co-cultures. Food Chemistry X. 29. 102745–102745. 1 indexed citations

3.

Huang, Wenke, et al.. (2025). Revisiting federated learning with label skew: an over-confidence perspective. Science China Information Sciences. 68(9). 1 indexed citations

4.

Huang, Wenke, Mang Ye, Zekun Shi, et al.. (2024). Federated Learning for Generalization, Robustness, Fairness: A Survey and Benchmark. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(12). 9387–9406. 56 indexed citations breakdown →

5.

Yang, Junhong, et al.. (2024). Quantitative detection of refrigerant charge faults in multi-unit air conditioning systems based on machine learning algorithms. International Journal of Refrigeration. 169. 184–193. 6 indexed citations

6.

Huang, Wenke, Mang Ye, Zekun Shi, & Bo Du. (2023). Generalizable Heterogeneous Federated Cross-Correlation and Instance Similarity Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(2). 712–728. 37 indexed citations

7.

Huang, Wenke, Mang Ye, Zekun Shi, Li He, & Bo Du. (2023). Rethinking Federated Learning with Domain Shift: A Prototype View. 16312–16322. 75 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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