Weiqi Wang

539 total citations
28 papers, 350 citations indexed

About

Weiqi Wang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Weiqi Wang has authored 28 papers receiving a total of 350 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 10 papers in Computer Vision and Pattern Recognition and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Weiqi Wang's work include Privacy-Preserving Technologies in Data (6 papers), Ultrasound Imaging and Elastography (4 papers) and Adversarial Robustness in Machine Learning (4 papers). Weiqi Wang is often cited by papers focused on Privacy-Preserving Technologies in Data (6 papers), Ultrasound Imaging and Elastography (4 papers) and Adversarial Robustness in Machine Learning (4 papers). Weiqi Wang collaborates with scholars based in China, Australia and Finland. Weiqi Wang's co-authors include An Liu, Yuanyuan Wang, Qing Li, Shuo Shang, Xiangliang Zhang, Yu Zhang, Tianyi Han, Xinchun Chen, Chenhui Zhang and Jinjin Li and has published in prestigious journals such as Applied Catalysis B: Environmental, The Journal of Physical Chemistry C and Small.

In The Last Decade

Weiqi Wang

17 papers receiving 340 citations

Peers

Weiqi Wang
Comparison fields: 5 of 78
  • Artificial Intelligence 84
  • Mechanics of Materials 66
  • Mechanical Engineering 59
  • Computer Vision and Pattern Recognition 49
  • Computer Science Applications 49
Replace Tianchen Wang with:
Tianchen Wang United States
Semen Budennyy Russia
Zixu Zhao China
Xin Huang China
Yifan Wang China
Dhiren Patel India
Yang Wen China
Tianchen Wang United States View profile →
Citations per field, relative to Weiqi Wang
Weiqi Wang · 1×
Citations per year, relative to Weiqi Wang
Weiqi Wang · 1×

Countries citing papers authored by Weiqi Wang

Since Specialization
Citations

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

Fields of papers citing papers by Weiqi Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Weiqi Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Weiqi Wang. A scholar is included among the top collaborators of Weiqi Wang 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 Weiqi Wang. Weiqi Wang 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 1
2 0
3 0
4 0
5 1
6 1
7 0
8 0
9 0
10 0
11 1
12 1
13 12
14 1
15 0
16 69
17 26
18 4
19 4
20 63

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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