Meng Wang

4.3k total citations · 1 hit paper
108 papers, 3.2k citations indexed

About

Meng Wang is a scholar working on Artificial Intelligence, Renewable Energy, Sustainability and the Environment and Materials Chemistry. According to data from OpenAlex, Meng Wang has authored 108 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Artificial Intelligence, 18 papers in Renewable Energy, Sustainability and the Environment and 18 papers in Materials Chemistry. Recurrent topics in Meng Wang's work include Advanced Graph Neural Networks (21 papers), Topic Modeling (20 papers) and Advanced Photocatalysis Techniques (17 papers). Meng Wang is often cited by papers focused on Advanced Graph Neural Networks (21 papers), Topic Modeling (20 papers) and Advanced Photocatalysis Techniques (17 papers). Meng Wang collaborates with scholars based in China, United States and Australia. Meng Wang's co-authors include Xindong Wu, Shaohua Shen, Dacheng Tao, Jun Yu, Penghui Guo, Jie Chen, Yue Gao, Xuelong Li, Zheng-Jun Zha and Liejin Guo and has published in prestigious journals such as Applied Physics Letters, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Meng Wang

100 papers receiving 3.1k citations

Hit Papers

Visual-Textual Joint Relevance Learning for Tag-Based Soc... 2012 2026 2016 2021 2012 100 200 300

Peers

Meng Wang
Comparison fields: 5 of 163
  • Materials Chemistry 958
  • Renewable Energy, Sustainability and the Environment 918
  • Computer Vision and Pattern Recognition 869
  • Artificial Intelligence 810
  • Electrical and Electronic Engineering 464
Replace Yu-Xiong Wang with:
Yu-Xiong Wang China
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Yu-Xiong Wang China View profile →
Citations per field, relative to Meng Wang
Meng Wang · 1×
Citations per year, relative to Meng Wang
Meng Wang · 1×

Countries citing papers authored by Meng Wang

Since Specialization
Citations

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

Fields of papers citing papers by Meng Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Meng Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Meng Wang. A scholar is included among the top collaborators of Meng 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 Meng Wang. Meng 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
# Work Indexed citations
1 2
2 3
3 1
4 0
5 1
6 4
7 16
8 4
9 11
10 0
11 10
12 3
13 5
14 3
15 3
16
Safe Medicine Recommendation via Medical Knowledge Graph Embedding
31
17 62
18
ANNA: Answering Why-Not Questions for SPARQL
2
19 39
20 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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