Yan Kang

837 total citations
31 papers, 405 citations indexed

About

Yan Kang is a scholar working on Artificial Intelligence, Materials Chemistry and Information Systems. According to data from OpenAlex, Yan Kang has authored 31 papers receiving a total of 405 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 6 papers in Materials Chemistry and 5 papers in Information Systems. Recurrent topics in Yan Kang's work include Privacy-Preserving Technologies in Data (5 papers), Stochastic Gradient Optimization Techniques (3 papers) and Sentiment Analysis and Opinion Mining (2 papers). Yan Kang is often cited by papers focused on Privacy-Preserving Technologies in Data (5 papers), Stochastic Gradient Optimization Techniques (3 papers) and Sentiment Analysis and Opinion Mining (2 papers). Yan Kang collaborates with scholars based in China, Hong Kong and Australia. Yan Kang's co-authors include Qiang Yang, Tianjian Chen, Yang Liu, Han Yu, Yong Cheng, Yuanqin He, Lixin Fan, Rong Pan, Jiahuan Luo and Yuezhou Wu and has published in prestigious journals such as Nature Communications, Electrochimica Acta and BMC Genomics.

In The Last Decade

Yan Kang

24 papers receiving 393 citations

Peers

Yan Kang
Comparison fields: 5 of 86
  • Artificial Intelligence 237
  • Electrical and Electronic Engineering 81
  • Materials Chemistry 56
  • Computer Networks and Communications 53
  • Information Systems 48
Replace Yuncheng Wu with:
Yuncheng Wu Singapore
Anran Li China
Yifeng Yin China
Dongwook Shin South Korea
Bang Liu China
Debin Liu China
Manisha Guduri India
Ruoxi Sun Australia
Yuncheng Wu Singapore View profile →
Citations per field, relative to Yan Kang
Yan Kang · 1×
Citations per year, relative to Yan Kang
Yan Kang · 1×

Countries citing papers authored by Yan Kang

Since Specialization
Citations

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

Fields of papers citing papers by Yan Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yan Kang

This figure shows the co-authorship network connecting the top 25 collaborators of Yan Kang. A scholar is included among the top collaborators of Yan Kang 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 Yan Kang. Yan Kang 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
# Work Indexed citations
1 0
2 0
3 0
4 0
5 1
6 0
7 2
8 1
9 57
10 4
11 5
12 45
13 34
14 11
15 152
16
A Communication Efficient Vertical Federated Learning Framework.
31
17 1
18 2
19 7
20
Simple analysis on Cloud Computing solutions of B2C e-commerce
1

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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