Zhao Cao

884 total citations
46 papers, 425 citations indexed

About

Zhao Cao is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Zhao Cao has authored 46 papers receiving a total of 425 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Artificial Intelligence, 18 papers in Computer Vision and Pattern Recognition and 12 papers in Information Systems. Recurrent topics in Zhao Cao's work include Topic Modeling (24 papers), Multimodal Machine Learning Applications (13 papers) and Natural Language Processing Techniques (12 papers). Zhao Cao is often cited by papers focused on Topic Modeling (24 papers), Multimodal Machine Learning Applications (13 papers) and Natural Language Processing Techniques (12 papers). Zhao Cao collaborates with scholars based in China, United Kingdom and United States. Zhao Cao's co-authors include Han Liu, Bill Roscoe, Zhong Chen, Chao Liu, Bangdao Chen, Zheng Liu, Yingxia Shao, Yanlei Diao, Prashant Shenoy and Zhicheng Dou and has published in prestigious journals such as Chemical Engineering Journal, Clinica Chimica Acta and IEEE Transactions on Knowledge and Data Engineering.

In The Last Decade

Zhao Cao

42 papers receiving 413 citations

Peers

Zhao Cao
Comparison fields: 5 of 67
  • Information Systems 214
  • Artificial Intelligence 200
  • Computer Vision and Pattern Recognition 109
  • Signal Processing 76
  • Computer Networks and Communications 61
Replace Tianqing Zhu with:
Tianqing Zhu China
Mustafa Al‐Fayoumi Jordan
Mudassir Khan Saudi Arabia
Wenguang Zheng China
Simona Ramanauskaitė Lithuania
Saša Adamović Serbia
Qingfeng Tan China
Matthias Baumgarten United Kingdom
Zakaria Elberrichi Algeria
Suryanti Awang Malaysia
Tianqing Zhu China View profile →
Citations per field, relative to Zhao Cao
Zhao Cao · 1×
Citations per year, relative to Zhao Cao
Zhao Cao · 1×

Countries citing papers authored by Zhao Cao

Since Specialization
Citations

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

Fields of papers citing papers by Zhao Cao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhao Cao

This figure shows the co-authorship network connecting the top 25 collaborators of Zhao Cao. A scholar is included among the top collaborators of Zhao Cao 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 Zhao Cao. Zhao Cao 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 2
3 1
4 1
5 1
6 0
7 2
8 1
9 4
10 5
11 7
12 10
13 7
14 2
15 2
16 2
17 9
18 9
19 33
20 3

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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