Chongzhi Wu

45 papers receiving 2.7k citations

Hit Papers

Prediction of undrained shear strength using extreme grad...201920262021202320202019202020202020200400600

Peers

Chongzhi Wu
Comparison fields: 5 of 139
  • Civil and Structural Engineering 1.7k
  • Safety, Risk, Reliability and Quality 1.1k
  • Management, Monitoring, Policy and Law 621
  • Mechanics of Materials 389
  • Mechanical Engineering 297
Replace Yong Liu with:
Yong Liu China
Wan‐Huan Zhou Macao
Mark B. Jaksa Australia
Kenneth Gavin Ireland
Robert Y. Liang United States
Hangseok Choi South Korea
Majidreza Nazem Australia
Yongqin Li China
Xu Li China
Chongzhi Wu relative to Yong Liu China Yong Liu's profile →
Citations per field
00.5×1.7×
Yong Liu · 1×
Citations per year

Countries citing papers authored by Chongzhi Wu

Since Specialization
Citations

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

Fields of papers citing papers by Chongzhi Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chongzhi Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Chongzhi Wu. A scholar is included among the top collaborators of Chongzhi Wu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Chongzhi Wu. Chongzhi Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
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Deep learning methods for time-dependent reliability analysis of reservoir slopes in spatially variable soilsbreakdown →
77
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Prediction of undrained shear strength using extreme gradient boosting and random forest based on Bayesian optimizationbreakdown →
662

About Chongzhi Wu

Chongzhi Wu is a scholar working on Safety, Risk, Reliability and Quality, Civil and Structural Engineering and Management, Monitoring, Policy and Law, having authored 48 papers that have together received 2.8k indexed citations. Recurring topics across this work include Geotechnical Engineering and Analysis (22 papers), Nanoplatforms for cancer theranostics (14 papers) and Dam Engineering and Safety (12 papers). The work is most often cited by research in Safety, Risk, Reliability and Quality (1.1k citations), Civil and Structural Engineering (1.7k citations) and Management, Monitoring, Policy and Law (621 citations). Chongzhi Wu has collaborated with scholars based in China, Singapore and Norway. Frequent co-authors include Wengang Zhang, Lin Wang, Yongqin Li, Anthony T.C. Goh, Hanlong Liu, Runhong Zhang, Suzanne Lacasse, Zhongqiang Liu, Libin Tang and Lin Wang. Their work appears in journals such as Journal of the American Chemical Society, Advanced Materials and Angewandte Chemie International Edition.

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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