Jun Yu

730 citations
53 papers · 602 · h-index 13

Impact in

Papers in

Jun Yu

47 papers receiving 565 citations

Peers

Jun Yu
Comparison fields: 5 of 75
  • Statistical and Nonlinear Physics 248
  • Mathematical Physics 130
  • Modeling and Simulation 53
  • Computational Theory and Mathematics 133
  • Numerical Analysis 39
Replace Jürgen Scheurle with:
Jürgen Scheurle Germany
R. Teman United States
Валерий Васильевич Козлов Russia
Chongchun Zeng United States
Masaya Yamaguti Japan
A. Eden Türkiye
Gianni Arioli Italy
V. A. Trenogin Russia
Hans Engler United States
S. M. Sun United States
Jun Yu relative to Jürgen Scheurle Germany Jürgen Scheurle's profile →
Citations per field
00.5×6.5×
Jürgen Scheurle · 1×
Citations per year

Countries citing papers authored by Jun Yu

Since Specialization
Citations

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

Fields of papers citing papers by Jun Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015130
2 201053
3 201240
4 199233
5 201533
6 199422
7 201622
8 200020
9 202318
10 201518
11 198917
12 199514
13 201513
14 201011
15 201311
16 201310
17 201210
18 20169
19 20169
20 19959

About Jun Yu

Jun Yu is a scholar working on Statistical and Nonlinear Physics, Mathematical Physics, Computer Networks and Communications, Computational Mechanics and Computational Theory and Mathematics, having authored 53 papers that have together received 602 indexed citations. Recurring topics across this work include Nonlinear Waves and Solitons (13 papers), Advanced Mathematical Modeling in Engineering (12 papers), Nonlinear Dynamics and Pattern Formation (12 papers), Nonlinear Photonic Systems (8 papers), Numerical methods in inverse problems (8 papers), Stability and Controllability of Differential Equations (7 papers), Advanced Mathematical Physics Problems (6 papers) and Combustion and flame dynamics (6 papers). The work is most often cited by research in Statistical and Nonlinear Physics (248 citations), Mathematical Physics (130 citations), Modeling and Simulation (53 citations), Computational Theory and Mathematics (133 citations) and Numerical Analysis (39 citations). Jun Yu has collaborated with scholars based in United States, China and Italy. Frequent co-authors include Wenjun Liu, Xing Lü, Wen‐Xiu Ma, Chaudry Masood Khalique, J. Kevorkian, Kewang Chen, Chenggui Yao, Qi Zhao, Isabelle Ragueneau‐Majlessi and Tasha K. Ritchie. Their work appears in journals such as Studies in Applied Mathematics, SIAM Journal on Applied Mathematics, Journal of Mathematical Analysis and Applications, Journal of Fluid Mechanics and Drug Metabolism and Disposition.

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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