Mingyang Li

762 citations
50 papers · 542 · h-index 15

Impact in

Papers in

Mingyang Li

41 papers receiving 530 citations

Peers

Mingyang Li
Comparison fields: 5 of 94
  • Statistics, Probability and Uncertainty 124
  • Safety, Risk, Reliability and Quality 125
  • Software 38
  • Statistics and Probability 60
  • Finance 48
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John Quigley United Kingdom
Rodrigo José Pires Ferreira Brazil
Lu Lu United States
A.Z. Keller United Kingdom
Mark P. Kaminskiy United States
Martin Newby United Kingdom
Michelle Kirby United States
Gianpaolo Di Bona Italy
Urho Pulkkinen Finland
Vasiliy Krivtsov United States
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Countries citing papers authored by Mingyang Li

Since Specialization
Citations

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

Fields of papers citing papers by Mingyang Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202096
2 201761
3 201958
4 201929
5 201825
6 201722
7 201821
8 201321
9 201720
10 201620
11 201619
12 202017
13 201917
14 201515
15 201714
16 202211
17 20179
18 20188
19 20167
20 20216

About Mingyang Li

Mingyang Li is a scholar working on Statistics, Probability and Uncertainty, Safety, Risk, Reliability and Quality, Civil and Structural Engineering, Statistics and Probability and Software, having authored 50 papers that have together received 542 indexed citations. Recurring topics across this work include Reliability and Maintenance Optimization (12 papers), Probabilistic and Robust Engineering Design (8 papers), Risk and Safety Analysis (6 papers), Statistical Distribution Estimation and Applications (6 papers), Software Reliability and Analysis Research (6 papers), Infrastructure Maintenance and Monitoring (4 papers), Financial Markets and Investment Strategies (3 papers) and Concrete Corrosion and Durability (3 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (124 citations), Safety, Risk, Reliability and Quality (125 citations), Software (38 citations), Statistics and Probability (60 citations) and Finance (48 citations). Mingyang Li has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Lu Lu, Wolfgang Karl Härdle, Yisha Xiang, Jian Liu, Qing Lu, Qingpei Hu, Xi Zhang, Qingpeng Zhang, Jingjing Li and Hui Wang. Their work appears in journals such as Reliability Engineering & System Safety, Quality Engineering, IEEE Transactions on Reliability, IISE Transactions and Neurocomputing.

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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