Menglu Yu

824 citations
24 papers · 531 · h-index 8

Impact in

Papers in

Menglu Yu

22 papers receiving 521 citations

Peers

Menglu Yu
Comparison fields: 5 of 78
  • Infectious Diseases 326
  • General Dentistry 20
  • Modeling and Simulation 29
  • Obstetrics and Gynecology 32
  • Neurology 51
Replace Kaku Tamura with:
Kaku Tamura Japan
Alireza Barzegary Iran
Neeraj G. Patel United States
Zhihua Lv China
Sara Perlman‐Arrow Canada
Paula Zambrano-Achig Ecuador
Hanyujie Kang China
Farzin Vahedi Iran
Frank Naujoks Germany
Menglu Yu relative to Kaku Tamura Japan Kaku Tamura's profile →
Citations per field
00.5×1.5×2.3×
Kaku Tamura · 1×
Citations per year

Countries citing papers authored by Menglu Yu

Since Specialization
Citations

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

Fields of papers citing papers by Menglu Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020379
2 202035
3 202223
4 202212
5 201912
6 202011
7 201810
8 20219
9 20237
10 20236
11 20226
12 20234
13 20213
14 20232
15 20242
16 20252
17 20252
18 20202
19 20211
20 20231

About Menglu Yu

Menglu Yu is a scholar working on Electrical and Electronic Engineering, Information Systems, Computer Networks and Communications, Artificial Intelligence and Biomedical Engineering, having authored 24 papers that have together received 531 indexed citations. Recurring topics across this work include solar cell performance optimization (10 papers), Chalcogenide Semiconductor Thin Films (7 papers), Cloud Computing and Resource Management (4 papers), Stochastic Gradient Optimization Techniques (3 papers), Nanowire Synthesis and Applications (3 papers), Silicon and Solar Cell Technologies (3 papers), IoT and Edge/Fog Computing (3 papers) and Thermal Radiation and Cooling Technologies (2 papers). The work is most often cited by research in Infectious Diseases (326 citations), General Dentistry (20 citations), Modeling and Simulation (29 citations), Obstetrics and Gynecology (32 citations) and Neurology (51 citations). Menglu Yu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Zhendong Tong, Peng Li, Jianbo Yan, Kefeng Li, An Tang, Hongling Wang, Yaxin Dai, Wenjie Wu, Bo Ji and Jia Liu. Their work appears in journals such as Emerging infectious diseases, IEEE Transactions on Network Science and Engineering, Nano Energy, Progress in Photovoltaics Research and Applications and IEEE Transactions on Electron Devices.

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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