Zixu Wang

540 citations
28 papers · 202 indexed · h-index 9
Topics
Computational Drug Discovery Methods (5 papers)Advanced biosensing and bioanalysis techniques (5 papers)Machine Learning in Materials Science (4 papers)
Partner nations
ChinaJapanSouth Korea

In The Last Decade

Zixu Wang

27 papers receiving 198 citations

Peers

Zixu Wang
Comparison fields: 5 of 72
  • Molecular Biology 79
  • Computer Vision and Pattern Recognition 51
  • Computational Theory and Mathematics 37
  • Materials Chemistry 26
  • Artificial Intelligence 25
Replace Md. Mohaiminul Islam with:
Md. Mohaiminul Islam Bangladesh
Zan Armstrong United States
Yilin Ye China
C. Wolfe United States
Yuqi Wang China
Jasper Zuallaert Belgium
Xiaoping Min China
Shazia Dharssi United States
Qinhu Zhang China
Zichang Xu Japan
Zixu Wang relative to Md. Mohaiminul Islam Bangladesh Md. Mohaiminul Islam's profile →
Citations per field
00.5×3.7×
Md. Mohaiminul Islam · 1×
Citations per year

Countries citing papers authored by Zixu Wang

Since Specialization
Citations

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

Fields of papers citing papers by Zixu Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zixu Wang

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

About Zixu Wang

Zixu Wang is a scholar working on Computational Theory and Mathematics, Computer Vision and Pattern Recognition and Electronic, Optical and Magnetic Materials, having authored 28 papers that have together received 202 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (5 papers), Advanced biosensing and bioanalysis techniques (5 papers) and Machine Learning in Materials Science (4 papers). The work is most often cited by research in Health Informatics (4 citations), Computer Vision and Pattern Recognition (51 citations) and Computational Theory and Mathematics (37 citations). Zixu Wang has collaborated with scholars based in China, Japan and South Korea. Frequent co-authors include Yangyang Chen, Xiucai Ye, Xiangxiang Zeng, Zhe Quan, Zhijie Wang, Lizhuang Liu, Tetsuya Sakurai, Pengyong Li, Na Li and Yang Zhang. Their work appears in journals such as Expert Systems with Applications, IEEE Access and Biosensors and Bioelectronics.

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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