Haiying Wang

456 citations
19 papers · 302 indexed · h-index 5
Topics
Advanced Numerical Methods in Computational Mathematics (6 papers)Advanced Mathematical Modeling in Engineering (3 papers)Statistical Methods and Inference (3 papers)
Partner nations
ChinaUnited States

In The Last Decade

Haiying Wang

16 papers receiving 281 citations

Peers

Haiying Wang
Comparison fields: 5 of 50
  • Computational Mechanics 201
  • Electrical and Electronic Engineering 79
  • Computational Theory and Mathematics 77
  • Mechanics of Materials 64
  • Statistics and Probability 62
Replace Pekka Neittaanmäki with:
Pekka Neittaanmäki Finland
Leszek Plaskota Poland
Arthur G. Werschulz United States
Rudolph A. Lorentz Germany
Allal Guessab France
Rémi Arcangéli France
Afet Golayoğlu Fatullayev Türkiye
J. B. Reade United Kingdom
Guohui Song United States
Toni Sayah Lebanon
Haiying Wang relative to Pekka Neittaanmäki Finland Pekka Neittaanmäki's profile →
Citations per field
00.5×5.3×
Pekka Neittaanmäki · 1×
Citations per year

Countries citing papers authored by Haiying Wang

Since Specialization
Citations

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

Fields of papers citing papers by Haiying Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Haiying Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Haiying Wang. A scholar is included among the top collaborators of Haiying Wang 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 Haiying Wang. Haiying Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
#WorkIndexed citations
1 0
2 1
3 1
4 78
5
Optimal Subsampling for Big Data Regressions
0
6 2
7 1
8 4
9
Simulation for Urban Population Distribution Based on GIS and Multi-agent
1
10 3
11 2
12 5
13 12
14 1
15 139
16 1
17 1
18 50
19
On the Single Physical Layer User Plane Architecture Network
0

About Haiying Wang

Haiying Wang is a scholar working on Numerical Analysis, Statistics and Probability and Computational Mechanics, having authored 19 papers that have together received 302 indexed citations. Recurring topics across this work include Advanced Numerical Methods in Computational Mathematics (6 papers), Advanced Mathematical Modeling in Engineering (3 papers) and Statistical Methods and Inference (3 papers). The work is most often cited by research in Numerical Analysis (53 citations), Computational Mechanics (201 citations) and Statistics and Probability (62 citations). Haiying Wang has collaborated with scholars based in China and United States. Frequent co-authors include Bernardo Cockburn, Johnny Guzmán, Huiming Zhang, Jun Yu, Mingyao Ai, Jay Gopalakrishnan, Simon Tavener, D. Estep, Michael Pernice and Guohua Zou. Their work appears in journals such as Journal of the American Statistical Association, Computer Methods in Applied Mechanics and Engineering and Mathematics of 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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