Ru Wang

488 citations
37 papers · 295 · h-index 11

Impact in

Papers in

Ru Wang

31 papers receiving 284 citations

Peers

Ru Wang
Comparison fields: 5 of 92
  • Human-Computer Interaction 31
  • Artificial Intelligence 127
  • Computer Vision and Pattern Recognition 80
  • Fuel Technology 2
  • Statistical and Nonlinear Physics 23
Replace Sabariah Baharun with:
Sabariah Baharun Malaysia
Venkatesan Ekambaram United States
Jyothisha J. Nair India
Mingyang Chen China
Tony Robinson United Kingdom
Danyang Huang China
Zhili Wu China
Li-Lun Wang United States
Shuang Yang China
Yiwei Wang Singapore
Ru Wang relative to Sabariah Baharun Malaysia Sabariah Baharun's profile →
Citations per field
00.5×4.5×
Sabariah Baharun · 1×
Citations per year

Countries citing papers authored by Ru Wang

Since Specialization
Citations

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

Fields of papers citing papers by Ru Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ru Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ru Wang Line = papers co-authored together Ru Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202233
2 202332
3 201431
4 202224
5 201618
6 202118
7 202117
8 202117
9 201716
10 202211
11 202310
12 201710
13 20219
14 20226
15 20246
16 20224
17 20224
18 20224
19 20214
20 20233

About Ru Wang

Ru Wang is a scholar working on Artificial Intelligence, Information Systems, Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition and Computational Theory and Mathematics, having authored 37 papers that have together received 295 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (6 papers), Recommender Systems and Techniques (5 papers), Advanced Graph Neural Networks (4 papers), Face and Expression Recognition (3 papers), Educational Technology and Assessment (3 papers), Online Learning and Analytics (3 papers), Nonlinear Partial Differential Equations (3 papers) and Hydrocarbon exploration and reservoir analysis (2 papers). The work is most often cited by research in Human-Computer Interaction (31 citations), Artificial Intelligence (127 citations), Computer Vision and Pattern Recognition (80 citations), Fuel Technology (2 citations) and Statistical and Nonlinear Physics (23 citations). Ru Wang has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Peipei Wang, Lin Li, Xiaohui Tao, Peiyu Liu, Lichun Wang, Baocai Yin, Dehui Kong, Qiang Li, Na Xu and Yan Zhao. Their work appears in journals such as International Journal of Emerging Technologies in Learning (iJET), Information Processing & Management, Information Sciences, Planta and Education and Information Technologies.

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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