Zhenyu Lu

104 papers receiving 1.7k citations

Peers

Zhenyu Lu
Comparison fields: 5 of 139
  • Process Chemistry and Technology 69
  • Catalysis 138
  • Artificial Intelligence 549
  • Computational Theory and Mathematics 234
  • Computer Vision and Pattern Recognition 216
Replace M. Srinivas with:
M. Srinivas India
Giorgio Valentini Italy
Lihong Guo China
Gang Xie China
Sebastian Mosbach United Kingdom
Guijun Wang United States
Bing Liu China
Jinlong Li China
Haoran Li China
Zhenyu Lu relative to M. Srinivas India M. Srinivas's profile →
Citations per field
00.5×4.2×
M. Srinivas · 1×
Citations per year

Countries citing papers authored by Zhenyu Lu

Since Specialization
Citations

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

Fields of papers citing papers by Zhenyu Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 120 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017119
2 202094
3 202088
4 201986
5 201973
6 202071
7 201864
8 202054
9 202250
10 202245
11 202341
12 201841
13 201535
14 201935
15 202034
16 201830
17 201829
18 202227
19 202227
20 201927

About Zhenyu Lu

Zhenyu Lu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Control and Systems Engineering and Computational Theory and Mathematics, having authored 120 papers that have together received 1.7k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (26 papers), Advanced Multi-Objective Optimization Algorithms (13 papers), Evolutionary Algorithms and Applications (13 papers), Molecular Sensors and Ion Detection (7 papers), Advanced Algorithms and Applications (6 papers), Covalent Organic Framework Applications (6 papers), Vehicle Routing Optimization Methods (6 papers) and Neural Networks Stability and Synchronization (6 papers). The work is most often cited by research in Process Chemistry and Technology (69 citations), Catalysis (138 citations), Artificial Intelligence (549 citations), Computational Theory and Mathematics (234 citations) and Computer Vision and Pattern Recognition (216 citations). Zhenyu Lu has collaborated with scholars based in China, South Korea and Taiwan. Frequent co-authors include Qiang Yang, Xudong Gao, Jun Zhang, Gongke Li, Runkun Zhang, Sang-Woon Jeon, Yufei Hu, Dongdong Xu, Mindong Chen and Junhao Hu. Their work appears in journals such as Remote Sensing, Expert Systems with Applications, IEEE Transactions on Cybernetics, Neurocomputing and Talanta.

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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