Zhengwei Bai

485 citations
23 papers · 285 indexed · h-index 8
Topics
Autonomous Vehicle Technology and Safety (10 papers)Advanced Neural Network Applications (6 papers)Innovative concrete reinforcement materials (4 papers)

In The Last Decade

Zhengwei Bai

20 papers receiving 282 citations

Peers

Zhengwei Bai
Comparison fields: 5 of 38
  • Automotive Engineering 175
  • Control and Systems Engineering 101
  • Computer Vision and Pattern Recognition 88
  • Electrical and Electronic Engineering 57
  • Building and Construction 37
Replace Yingjuan Tang with:
Yingjuan Tang China
Daniel Goehring Germany
Benjamin Caine Germany
Hossein Tehrani Japan
Zoey Yang Germany
Phillip Karle Germany
Chenxi Liu China
Antonio Prioletti Italy
Matthias Goebl Germany
Kay Fuerstenberg Germany
Zhengwei Bai relative to Yingjuan Tang China Yingjuan Tang's profile →
Citations per field
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Yingjuan Tang · 1×
Citations per year

Countries citing papers authored by Zhengwei Bai

Since Specialization
Citations

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

Fields of papers citing papers by Zhengwei Bai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhengwei Bai

This figure shows the co-authorship network connecting the top 25 collaborators of Zhengwei Bai. A scholar is included among the top collaborators of Zhengwei 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 Zhengwei Bai. Zhengwei Bai 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
#WorkIndexed citations
1 0
2 0
3 0
4 1
5 3
6 1
7 10
8 4
9 2
10 4
11 7
12 9
13 1
14 1
15 8
16 95
17 2
18 11
19 2
20 26

About Zhengwei Bai

Zhengwei Bai is a scholar working on Automotive Engineering, General Engineering and Building and Construction, having authored 23 papers that have together received 285 indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (10 papers), Advanced Neural Network Applications (6 papers) and Innovative concrete reinforcement materials (4 papers). The work is most often cited by research in Automotive Engineering (175 citations), Control and Systems Engineering (101 citations) and Computer Vision and Pattern Recognition (88 citations). Zhengwei Bai has collaborated with scholars based in China, United States and Switzerland. Frequent co-authors include Matthew Barth, Wei Shangguan, Baigen Cai, Guoyuan Wu, Kentaro Oguchi, Peng Hao, Emrah Akin Sisbot, Matthew J. Barth, Xuewei Qi and Linguo Chai. Their work appears in journals such as SHILAP Revista de lepidopterología, Construction and Building Materials and IEEE Transactions on Intelligent Transportation Systems.

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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