Jun-Feng Yin

826 citations
24 papers · 636 indexed · h-index 10
Topics
Matrix Theory and Algorithms (22 papers)Advanced Optimization Algorithms Research (11 papers)Iterative Methods for Nonlinear Equations (9 papers)
Partner nations
ChinaJapanUnited Kingdom

In The Last Decade

Jun-Feng Yin

22 papers receiving 598 citations

Peers

Jun-Feng Yin
Comparison fields: 5 of 42
  • Computational Theory and Mathematics 569
  • Numerical Analysis 401
  • Atomic and Molecular Physics, and Optics 240
  • Computational Mechanics 189
  • Algebra and Number Theory 41
Replace Naimin Zhang with:
Naimin Zhang China
Gunhild Lindskog Sweden
Cristina Tablino–Possio Italy
Shu-Qian Shen China
Fabio Di Benedetto Italy
Rafikul Alam India
Vjeran Hari Croatia
Julio Moro Spain
Zhongyun Liu China
Jun-Feng Yin relative to Naimin Zhang China Naimin Zhang's profile →
Citations per field
00.5×5.1×
Naimin Zhang · 1×
Citations per year

Countries citing papers authored by Jun-Feng Yin

Since Specialization
Citations

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

Fields of papers citing papers by Jun-Feng Yin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jun-Feng Yin. 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 Jun-Feng Yin. The network helps show where Jun-Feng Yin may publish in the future.

Co-authorship network of co-authors of Jun-Feng Yin

This figure shows the co-authorship network connecting the top 25 collaborators of Jun-Feng Yin. A scholar is included among the top collaborators of Jun-Feng Yin 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 Jun-Feng Yin. Jun-Feng Yin 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 1
3 2
4 8
5 16
6 6
7 31
8 28
9 36
10 2
11 127
12 6
13 0
14 34
15 9
16 1
17 9
18 13
19 264
20
ON TWO ITERATION METHODS FOR THE QUADRATIC MATRIX EQUATION
17

About Jun-Feng Yin

Jun-Feng Yin is a scholar working on Numerical Analysis, Computational Theory and Mathematics and Computational Mechanics, having authored 24 papers that have together received 636 indexed citations. Recurring topics across this work include Matrix Theory and Algorithms (22 papers), Advanced Optimization Algorithms Research (11 papers) and Iterative Methods for Nonlinear Equations (9 papers). The work is most often cited by research in Numerical Analysis (401 citations), Computational Theory and Mathematics (569 citations) and Computational Mathematics (9 citations). Jun-Feng Yin has collaborated with scholars based in China, Japan and United Kingdom. Frequent co-authors include Ning Zheng, Zhong‐Zhi Bai, Linzhang Lu, Gene H. Golub, Ken Hayami, Rui Li, Rui Li, Xiaoxia Guo, Iain Duff and Zengqi Wang. Their work appears in journals such as Food Chemistry, Applied Mathematics and Computation and SIAM Journal on Scientific Computing.

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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