Jinyun Yuan

2.0k citations
84 papers · 1.5k indexed · h-index 19
Topics
Matrix Theory and Algorithms (25 papers)Advanced Optimization Algorithms Research (24 papers)Advanced Numerical Methods in Computational Mathematics (22 papers)
Partner nations
BrazilChinaUnited States

In The Last Decade

Jinyun Yuan

77 papers receiving 1.4k citations

Peers

Jinyun Yuan
Comparison fields: 5 of 78
  • Computational Theory and Mathematics 599
  • Numerical Analysis 598
  • Computational Mechanics 588
  • Electrical and Electronic Engineering 323
  • Atomic and Molecular Physics, and Optics 311
Replace Joost Rommes with:
Joost Rommes Netherlands
Ioannis Dassios Ireland
Neculai Andrei Romania
Sandra A. Santos Brazil
Chyi Hwang Taiwan
Gonglin Yuan China
Zoran Gajić United States
Boris Vexler Germany
Pablo Pedregal Spain
Jinyun Yuan relative to Joost Rommes Netherlands Joost Rommes's profile →
Citations per field
00.5×6.6×
Joost Rommes · 1×
Citations per year

Countries citing papers authored by Jinyun Yuan

Since Specialization
Citations

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

Fields of papers citing papers by Jinyun Yuan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jinyun Yuan

This figure shows the co-authorship network connecting the top 25 collaborators of Jinyun Yuan. A scholar is included among the top collaborators of Jinyun Yuan 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 Jinyun Yuan. Jinyun Yuan 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
1 1
2 2
3 1
4 0
5 2
6 0
7 4
8 31
9 2
10 22
11 47
12 3
13 1
14 1
15 14
16 3
17 91
18 6
19 27
20 1

About Jinyun Yuan

Jinyun Yuan is a scholar working on Numerical Analysis, Computational Mathematics and Computational Theory and Mathematics, having authored 84 papers that have together received 1.5k indexed citations. Recurring topics across this work include Matrix Theory and Algorithms (25 papers), Advanced Optimization Algorithms Research (24 papers) and Advanced Numerical Methods in Computational Mathematics (22 papers). The work is most often cited by research in Numerical Analysis (598 citations), Computational Theory and Mathematics (599 citations) and Computational Mechanics (588 citations). Jinyun Yuan has collaborated with scholars based in Brazil, China and United States. Frequent co-authors include Xiaonan Wu, Gene H. Golub, Tong Zhang, Ya-xiang Yuan, Fugui Dong, Huanhuan Li, Liwei Ju, Zhongfu Tan, Qingkun Tan and Yu‐Hong Dai. Their work appears in journals such as Journal of Computational Physics, Applied Energy and International Journal of Heat and Mass Transfer.

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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