Shuai Meng

3.3k citations
122 papers · 2.3k · 1 hit paper · h-index 27

Impact in

Papers in

Shuai Meng

115 papers receiving 2.3k citations

Shuai Meng's Hit Papers

MIONet: Learning Multiple-Input Operators via Tensor Product 2022 · 130 citations
1300+1+2Years since publication4080120

Peers

Shuai Meng
Comparison fields: 5 of 152
  • Cancer Research 289
  • Computational Mechanics 289
  • Molecular Biology 756
  • Organic Chemistry 282
  • Control and Systems Engineering 230
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Shuai Meng relative to Changyi Wang China Changyi Wang's profile →
Citations per field
00.5×10×13.4×
Changyi Wang · 1×
Citations per year

Countries citing papers authored by Shuai Meng

Since Specialization
Citations

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

Fields of papers citing papers by Shuai Meng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Shuai Meng, 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 Shuai Meng Line = papers co-authored together Shuai Meng links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 122 papers — load more, or switch the sort, to bring in the rest.

#Work
1
MIONet: Learning Multiple-Input Operators via Tensor Product
Hit paper breakdown →
2022130
2 2017125
3 201695
4 201593
5 201091
6 201689
7 201481
8 201773
9 201769
10 201662
11 201754
12 201753
13 201251
14 201649
15 201648
16 202146
17 201745
18 201844
19 201643
20 201041

About Shuai Meng

Shuai Meng is a scholar working on Molecular Biology, Control and Systems Engineering, Computational Mechanics, Organic Chemistry and Plant Science, having authored 122 papers that have together received 2.3k indexed citations. Recurring topics across this work include Vibration and Dynamic Analysis (15 papers), Fluid Dynamics and Vibration Analysis (15 papers), Carbohydrate Chemistry and Synthesis (12 papers), Glycosylation and Glycoproteins Research (11 papers), Plant-Microbe Interactions and Immunity (7 papers), Wind and Air Flow Studies (7 papers), Geotechnical Engineering and Underground Structures (7 papers) and Fungal and yeast genetics research (7 papers). The work is most often cited by research in Cancer Research (289 citations), Computational Mechanics (289 citations), Molecular Biology (756 citations), Organic Chemistry (282 citations) and Control and Systems Engineering (230 citations). Shuai Meng has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Xiao Wang, Liping Xie, Xiangyi Zheng, Zhen Liang, Weijing Zhang, Pengzhan Jin, Lu Lu, Xin Xu, Jiangfeng Li and Alin Ji. Their work appears in journals such as Ocean Engineering, Oncotarget, The Journal of Organic Chemistry, Cell Death and Disease and Frontiers in Microbiology.

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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