Xueying Wang

631 citations
54 papers · 345 indexed · h-index 10
Topics
Advanced Neural Network Applications (16 papers)Advanced Memory and Neural Computing (4 papers)Neuroscience and Neural Engineering (4 papers)

In The Last Decade

Xueying Wang

46 papers receiving 325 citations

Peers

Xueying Wang
Comparison fields: 5 of 104
  • Computer Vision and Pattern Recognition 96
  • Artificial Intelligence 94
  • Computer Networks and Communications 46
  • Information Systems 44
  • Electrical and Electronic Engineering 43
Replace Fan Deng with:
Fan Deng China
Weiwei Yang China
Ankit Patel United States
Masaaki Nishino Japan
Tiago Pimentel Switzerland
Kailong Chen China
Anran Li China
Xueying Wang relative to Fan Deng China Fan Deng's profile →
Citations per field
00.5×5.4×
Fan Deng · 1×
Citations per year

Countries citing papers authored by Xueying Wang

Since Specialization
Citations

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

Fields of papers citing papers by Xueying Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xueying Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Xueying Wang. A scholar is included among the top collaborators of Xueying 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 Xueying Wang. Xueying 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 0
3 1
4 0
5 6
6 0
7 0
8 5
9 0
10 25
11 7
12 2
13 38
14 2
15 2
16 2
17 31
18 8
19 1
20
A View from Within: A Case Study of Chinese Heritage Community Language Schools in the United States.
41

About Xueying Wang

Xueying Wang is a scholar working on Computational Mathematics, Computer Vision and Pattern Recognition and Hardware and Architecture, having authored 54 papers that have together received 345 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (16 papers), Advanced Memory and Neural Computing (4 papers) and Neuroscience and Neural Engineering (4 papers). The work is most often cited by research in Computational Mathematics (4 citations), Linguistics and Language (28 citations) and Computer Vision and Pattern Recognition (96 citations). Xueying Wang has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Guangli Li, Lei Liu, Xiaobing Feng, Xiu Ma, Jingling Xue, Jiansong Li, Yizhou Wu, Zhongyi Jiang, Yang Zhao and Jiafu Shi. Their work appears in journals such as SHILAP Revista de lepidopterología, Earth and Planetary Science Letters and International Journal of Molecular Sciences.

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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