Wei Dai

2.5k citations
174 papers · 1.8k · h-index 23

Impact in

Papers in

Wei Dai

154 papers receiving 1.7k citations

Peers

Wei Dai
Comparison fields: 5 of 133
  • Industrial and Manufacturing Engineering 207
  • Statistics, Probability and Uncertainty 142
  • Safety, Risk, Reliability and Quality 150
  • Mechanical Engineering 594
  • Medical Laboratory Technology 23
Replace Jiajie Fan with:
Jiajie Fan China
Michael H. Azarian United States
Renjie Ji China
Jiaxin Zhang China
Shuai Zhao China
Tadahiro Shibutani Japan
Huai Wang Denmark
Hyunseok Oh South Korea
Jiaxu Wang China
Wei Dai relative to Jiajie Fan China Jiajie Fan's profile →
Citations per field
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Jiajie Fan · 1×
Citations per year

Countries citing papers authored by Wei Dai

Since Specialization
Citations

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

Fields of papers citing papers by Wei Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 174 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202281
2 201478
3 201975
4 201163
5 202452
6 201439
7 201439
8 202037
9 201636
10 201434
11 202333
12 202333
13 201830
14 201430
15 202028
16 201527
17 202027
18 201726
19 201926
20 202224

About Wei Dai

Wei Dai is a scholar working on Mechanical Engineering, Industrial and Manufacturing Engineering, Mechanics of Materials, Control and Systems Engineering and Safety, Risk, Reliability and Quality, having authored 174 papers that have together received 1.8k indexed citations. Recurring topics across this work include Manufacturing Process and Optimization (27 papers), Reliability and Maintenance Optimization (18 papers), Machine Fault Diagnosis Techniques (16 papers), Advanced machining processes and optimization (16 papers), Fault Detection and Control Systems (15 papers), Industrial Vision Systems and Defect Detection (10 papers), Fatigue and fracture mechanics (10 papers) and Advanced Fiber Optic Sensors (9 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (207 citations), Statistics, Probability and Uncertainty (142 citations), Safety, Risk, Reliability and Quality (150 citations), Mechanical Engineering (594 citations) and Medical Laboratory Technology (23 citations). Wei Dai has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Weifang Zhang, Yiqing Yang, Qiang Liu, Xiaowei Chen, Yihai He, Xuerong Liu, Yu Zhao, Meng Zhang, Weitao Lou and Ning Li. Their work appears in journals such as Materials, Sensors, Metals, IEEE Access and Applied Sciences.

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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