Dan Wu

1.5k citations
81 papers · 1.2k · h-index 19

Impact in

Papers in

Dan Wu

67 papers receiving 1.2k citations

Peers

Dan Wu
Comparison fields: 5 of 144
  • Safety, Risk, Reliability and Quality 231
  • Aerospace Engineering 393
  • Statistics, Probability and Uncertainty 102
  • Mechanics of Materials 207
  • Health, Toxicology and Mutagenesis 109
Replace Kaili Xu with:
Kaili Xu China
Xinmin Zhang China
Xin Yi He United States
Jiansong Wu China
Wei Tao Zhao China
Moshood Onifade South Africa
Zongxin Wu China
Xiaoshan Lin Australia
Bekir Genc South Africa
Dan Wu relative to Kaili Xu China Kaili Xu's profile →
Citations per field
00.5×5×10.8×
Kaili Xu · 1×
Citations per year

Countries citing papers authored by Dan Wu

Since Specialization
Citations

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

Fields of papers citing papers by Dan Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 81 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015181
2 201495
3 199262
4 201460
5 202252
6 201445
7 201543
8 201642
9 200941
10 201441
11 201440
12 202237
13 201837
14 202024
15 201124
16 201724
17 202322
18 202121
19 201619
20 201115

About Dan Wu

Dan Wu is a scholar working on Health, Toxicology and Mutagenesis, Economics and Econometrics, Information Systems, Computer Networks and Communications and Aerospace Engineering, having authored 81 papers that have together received 1.2k indexed citations. Recurring topics across this work include Air Quality and Health Impacts (8 papers), Energy, Environment, Economic Growth (7 papers), Climate Change Policy and Economics (7 papers), Semantic Web and Ontologies (7 papers), Plant Gene Expression Analysis (6 papers), Service-Oriented Architecture and Web Services (6 papers), Combustion and Detonation Processes (5 papers) and Meat and Animal Product Quality (4 papers). The work is most often cited by research in Safety, Risk, Reliability and Quality (231 citations), Aerospace Engineering (393 citations), Statistics, Probability and Uncertainty (102 citations), Mechanics of Materials (207 citations) and Health, Toxicology and Mutagenesis (109 citations). Dan Wu has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Jianping Wang, Rui Zhou, Shiqiu Zhang, Yuan Xu, Rafiqul Gani, Yan Liu, Meng Liu, Tong Fei Zhu, Yan Liu and Songbai Yao. Their work appears in journals such as Food Chemistry, Journal of Cleaner Production, Sustainability, Photodiagnosis and Photodynamic Therapy and Computers & Chemical Engineering.

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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