Ruiqi Wang

507 total citations
36 papers, 305 citations indexed

About

Ruiqi Wang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Social Psychology. According to data from OpenAlex, Ruiqi Wang has authored 36 papers receiving a total of 305 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 12 papers in Computer Vision and Pattern Recognition and 5 papers in Social Psychology. Recurrent topics in Ruiqi Wang's work include Domain Adaptation and Few-Shot Learning (6 papers), Multimodal Machine Learning Applications (5 papers) and Human Pose and Action Recognition (5 papers). Ruiqi Wang is often cited by papers focused on Domain Adaptation and Few-Shot Learning (6 papers), Multimodal Machine Learning Applications (5 papers) and Human Pose and Action Recognition (5 papers). Ruiqi Wang collaborates with scholars based in China, United States and Australia. Ruiqi Wang's co-authors include Xu-Yao Zhang, Cheng‐Lin Liu, Qiang Zhang, Xinxiao Wu, Byung‐Cheol Min, Zhujun Jing, Jiebo Luo, Yang Gao, Lei Qi and Fei Zhu and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Pattern Recognition.

In The Last Decade

Ruiqi Wang

31 papers receiving 292 citations

Peers

Ruiqi Wang
Comparison fields: 5 of 94
  • Artificial Intelligence 114
  • Computer Vision and Pattern Recognition 103
  • Environmental Engineering 41
  • Water Science and Technology 38
  • Control and Systems Engineering 22
Replace Marc Stöttinger with:
Marc Stöttinger Germany
Jian Shu China
Jianping Zhao China
Xuelian Deng China
Xiaochuan Sun China
Rajendra Prasath India
Yingqi Li China
Marc Stöttinger Germany View profile →
Citations per field, relative to Ruiqi Wang
Ruiqi Wang · 1×
Citations per year, relative to Ruiqi Wang
Ruiqi Wang · 1×

Countries citing papers authored by Ruiqi Wang

Since Specialization
Citations

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

Fields of papers citing papers by Ruiqi Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ruiqi Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Ruiqi Wang. A scholar is included among the top collaborators of Ruiqi 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 Ruiqi Wang. Ruiqi 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 0
2 0
3 0
4 1
5 0
6 1
7 11
8 1
9 5
10 8
11 10
12 54
13 10
14 42
15 11
16 21
17 4
18 1
19 7
20 16

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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