Dingcheng Wang

877 citations
69 papers · 629 · h-index 15

Impact in

Papers in

Dingcheng Wang

65 papers receiving 594 citations

Peers

Dingcheng Wang
Comparison fields: 5 of 89
  • Management Science and Operations Research 394
  • Finance 263
  • Demography 244
  • Statistics and Probability 74
  • Mathematical Physics 78
Replace Małgorzata M. O’Reilly with:
Małgorzata M. O’Reilly Australia
Reiichiro Kawai Japan
Qingshuo Song United States
Xunjing Li China
S. Ravi India
Xinpeng Li China
John W. Lau Australia
Aimé Lachapelle France
Mojtaba Nourian Canada
Dingcheng Wang relative to Małgorzata M. O’Reilly Australia Małgorzata M. O’Reilly's profile →
Citations per field
00.5×10×16.3×
Małgorzata M. O’Reilly · 1×
Citations per year

Countries citing papers authored by Dingcheng Wang

Since Specialization
Citations

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

Fields of papers citing papers by Dingcheng Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 69 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200665
2 200540
3 200940
4 199138
5 201729
6 201625
7 200421
8 202019
9 202119
10 201417
11 201517
12 201616
13
Moment complete convergence for sums of a sequence of NA random variables
200615
14 202114
15 201214
16 201113
17 201913
18 201311
19 201711
20 201610

About Dingcheng Wang

Dingcheng Wang is a scholar working on Management Science and Operations Research, Finance, Demography, Mathematical Physics and Statistics and Probability, having authored 69 papers that have together received 629 indexed citations. Recurring topics across this work include Probability and Risk Models (45 papers), Insurance, Mortality, Demography, Risk Management (24 papers), Financial Risk and Volatility Modeling (23 papers), Stochastic processes and statistical mechanics (12 papers), Stochastic processes and financial applications (10 papers), Random Matrices and Applications (7 papers), Insurance and Financial Risk Management (6 papers) and Statistical Distribution Estimation and Applications (6 papers). The work is most often cited by research in Management Science and Operations Research (394 citations), Finance (263 citations), Demography (244 citations), Statistics and Probability (74 citations) and Mathematical Physics (78 citations). Dingcheng Wang has collaborated with scholars based in China, Australia and Taiwan. Frequent co-authors include Qihe Tang, C. C. Heyde, Qunying Wu, Qingxia Zhang, Jie Huang, Ting‐Zhu Huang, Shih‐Tung Liu, Shu‐Fen Chang, Yu‐Sun Chang and Jing Chen. Their work appears in journals such as Journal of Inequalities and Applications, Advances in Applied Probability, Science China Mathematics, Journal of Applied Probability and International Journal of Environmental Research and Public Health.

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.

Explore authors with similar magnitude of impact