Jiawang Bai

527 total citations
11 papers, 135 citations indexed

About

Jiawang Bai is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Jiawang Bai has authored 11 papers receiving a total of 135 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 6 papers in Artificial Intelligence and 1 paper in Computer Networks and Communications. Recurrent topics in Jiawang Bai's work include Adversarial Robustness in Machine Learning (4 papers), Multimodal Machine Learning Applications (2 papers) and Advanced Neural Network Applications (2 papers). Jiawang Bai is often cited by papers focused on Adversarial Robustness in Machine Learning (4 papers), Multimodal Machine Learning Applications (2 papers) and Advanced Neural Network Applications (2 papers). Jiawang Bai collaborates with scholars based in China and Singapore. Jiawang Bai's co-authors include Shu‐Tao Xia, Yong Jiang, Yiming Li, Jiawei Li, Xue Yang, Baoyuan Wu, Xuan Wang, Zhifeng Li, Bin Chen and Tao Dai 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

Jiawang Bai

8 papers receiving 135 citations

Peers

Jiawang Bai
Comparison fields: 5 of 72
  • Artificial Intelligence 62
  • Computer Vision and Pattern Recognition 34
  • Signal Processing 16
  • Biomedical Engineering 13
  • Computer Networks and Communications 12
Replace Marcin Gabryel with:
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Zhiqiang Tang China
Gurram Sunitha India
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Vikash Sehwag United States
Yutaro Yamada Japan
Qing Sun China
Hong Qi China
Sanjay Kumar Sonbhadra India
Marcin Gabryel Poland View profile →
Citations per field, relative to Jiawang Bai
Jiawang Bai · 1×
Citations per year, relative to Jiawang Bai
Jiawang Bai · 1×

Countries citing papers authored by Jiawang Bai

Since Specialization
Citations

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

Fields of papers citing papers by Jiawang Bai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiawang Bai

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

All Works

11 of 11 papers shown
# Work Indexed citations
1 0
2 0
3 5
4 7
5 19
6 12
7 0
8 20
9 5
10 66
11 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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