Guangchen Wang

2.4k citations
91 papers · 1.7k · h-index 23

Impact in

Papers in

Guangchen Wang

79 papers receiving 1.6k citations

Peers

Guangchen Wang
Comparison fields: 5 of 80
  • Finance 917
  • Modeling and Simulation 246
  • Demography 375
  • Management Science and Operations Research 407
  • Industrial and Manufacturing Engineering 235
Replace Maarten H. van der Vlerk with:
Maarten H. van der Vlerk Netherlands
Gonçalo dos Reis United Kingdom
Goutam Dutta India
Ahmad M. Alshamrani Saudi Arabia
Sajid Ali Pakistan
Guglielmo D’Amico Italy
Yincai Tang China
Bernardo K. Pagnoncelli Chile
Francesca Maggioni Italy
Showkat Ahmad Lone Saudi Arabia
Guangchen Wang relative to Maarten H. van der Vlerk Netherlands Maarten H. van der Vlerk's profile →
Citations per field
00.5×10×20×30×41×
Maarten H. van der Vlerk · 1×
Citations per year

Countries citing papers authored by Guangchen Wang

Since Specialization
Citations

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

Fields of papers citing papers by Guangchen Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 91 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020110
2 2021107
3 201590
4 202286
5 201386
6 200973
7 201572
8 201369
9 201166
10 201063
11 200855
12 201747
13 202247
14 201842
15 200941
16 201739
17 201737
18 201837
19 202127
20 201026

About Guangchen Wang

Guangchen Wang is a scholar working on Finance, Management Science and Operations Research, Demography, Control and Systems Engineering and Economics and Econometrics, having authored 91 papers that have together received 1.7k indexed citations. Recurring topics across this work include Stochastic processes and financial applications (60 papers), Risk and Portfolio Optimization (34 papers), Insurance, Mortality, Demography, Risk Management (29 papers), Economic theories and models (11 papers), Mathematical Biology Tumor Growth (9 papers), Scheduling and Optimization Algorithms (5 papers), Asphalt Pavement Performance Evaluation (5 papers) and Advanced Manufacturing and Logistics Optimization (5 papers). The work is most often cited by research in Finance (917 citations), Modeling and Simulation (246 citations), Demography (375 citations), Management Science and Operations Research (407 citations) and Industrial and Manufacturing Engineering (235 citations). Guangchen Wang has collaborated with scholars based in China, Hong Kong and Macao. Frequent co-authors include Jie Xiong, Zhen Wu, Zhiyong Yu, Jingtao Shi, Jianhui Huang, Liang Gao, Xinyu Li, Chenghui Zhang, Peigen Li and Weihai Zhang. Their work appears in journals such as IEEE Transactions on Automatic Control, Automatica, Science China Information Sciences, Systems & Control Letters and Applied Mathematics and Computation.

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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