Jin Cui

1.5k citations
60 papers · 1.1k · 1 hit paper · h-index 12

Impact in

Papers in

Jin Cui

52 papers receiving 1.0k citations

Jin Cui's Hit Papers

Bearing remaining useful life prediction based on deep autoencoder and deep neural networks 2018 · 307 citations
3070+2+5Years since publication100200300

Peers

Jin Cui
Comparison fields: 5 of 106
  • Control and Systems Engineering 554
  • Medical Laboratory Technology 32
  • Industrial and Manufacturing Engineering 205
  • Safety, Risk, Reliability and Quality 164
  • Mechanical Engineering 330
Replace Kamran Javed with:
Kamran Javed Pakistan
Yafei Deng China
Shuai Zheng China
Yuanhang Wang China
Huawei Wang China
Yu Zheng China
Liangwei Zhang China
Samir Khan United Kingdom
Van Tung Tran South Korea
Zheng Zhou China
Jin Cui relative to Kamran Javed Pakistan Kamran Javed's profile →
Citations per field
00.5×1.5×1.8×
Kamran Javed · 1×
Citations per year

Countries citing papers authored by Jin Cui

Since Specialization
Citations

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

Fields of papers citing papers by Jin Cui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 60 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Bearing remaining useful life prediction based on deep autoencoder and deep neural networks
Hit paper breakdown →
2018307
2 2017233
3 2018133
4 202140
5 202237
6 202236
7 201933
8 201631
9 201523
10 202113
11 202011
12 202211
13 202211
14 201710
15 20239
16 20239
17 20219
18 20218
19 20158
20 20236

About Jin Cui

Jin Cui is a scholar working on Control and Systems Engineering, Mechanical Engineering, Computational Mechanics, Biomedical Engineering and Industrial and Manufacturing Engineering, having authored 60 papers that have together received 1.1k indexed citations. Recurring topics across this work include Machine Fault Diagnosis Techniques (12 papers), Fluid Dynamics and Vibration Analysis (10 papers), Fluid Dynamics and Turbulent Flows (7 papers), Digital Transformation in Industry (6 papers), Gear and Bearing Dynamics Analysis (6 papers), Fault Detection and Control Systems (5 papers), Engineering Diagnostics and Reliability (5 papers) and Industrial Vision Systems and Defect Detection (4 papers). The work is most often cited by research in Control and Systems Engineering (554 citations), Medical Laboratory Technology (32 citations), Industrial and Manufacturing Engineering (205 citations), Safety, Risk, Reliability and Quality (164 citations) and Mechanical Engineering (330 citations). Jin Cui has collaborated with scholars based in China, Australia and Canada. Frequent co-authors include Lei Ren, Yaqiang Sun, Zhang Li, Xuejun Cheng, Xiaokang Wang, Lin Zhang, Yongchang Wei, Pai Zheng, Jingeng Mai and Yisheng Lv. Their work appears in journals such as Applied Sciences, IEEE Sensors Journal, Engineering Computations, Journal of Manufacturing Systems and Future Generation Computer Systems.

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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