Jun Yan

1.4k citations
103 papers · 899 · h-index 17

Impact in

Papers in

Jun Yan

97 papers receiving 852 citations

Peers

Jun Yan
Comparison fields: 5 of 92
  • Statistical and Nonlinear Physics 278
  • Industrial and Manufacturing Engineering 127
  • Pollution 120
  • Applied Mathematics 108
  • Mathematical Physics 90
Replace V.S. Manoranjan with:
V.S. Manoranjan United States
Qiang Xi China
Kexue Li China
T. R. Marchant Australia
A. Cloot South Africa
Yujun Cui China
Konrad Bajer Poland
Prashant Pandey India
Yuwen Wang China
Jun Yan relative to V.S. Manoranjan United States V.S. Manoranjan's profile →
Citations per field
00.5×5×10.5×
V.S. Manoranjan · 1×
Citations per year

Countries citing papers authored by Jun Yan

Since Specialization
Citations

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

Fields of papers citing papers by Jun Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 103 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202178
2 200471
3 202252
4 202350
5 200941
6 201636
7 199832
8 201832
9 202021
10 202220
11 201020
12 202218
13 202018
14 201918
15 202417
16 201117
17 201616
18 200615
19 202215
20 201313

About Jun Yan

Jun Yan is a scholar working on Statistical and Nonlinear Physics, Control and Systems Engineering, Mathematical Physics, Industrial and Manufacturing Engineering and Atomic and Molecular Physics, and Optics, having authored 103 papers that have together received 899 indexed citations. Recurring topics across this work include Quantum chaos and dynamical systems (25 papers), Constructed Wetlands for Wastewater Treatment (10 papers), Industrial Technology and Control Systems (9 papers), Cosmology and Gravitation Theories (7 papers), Physics of Superconductivity and Magnetism (7 papers), Geometric Analysis and Curvature Flows (7 papers), Advanced Sensor and Control Systems (7 papers) and Wastewater Treatment and Nitrogen Removal (7 papers). The work is most often cited by research in Statistical and Nonlinear Physics (278 citations), Industrial and Manufacturing Engineering (127 citations), Pollution (120 citations), Applied Mathematics (108 citations) and Mathematical Physics (90 citations). Jun Yan has collaborated with scholars based in China, United States and Italy. Frequent co-authors include Chong-Qing Cheng, Kaizhi Wang, Lin Wang, Jianqiang Zhu, Dongliang Qi, Yi Chen, Qixia Wu, Xuebin Hu, Sung Kyu Choi and Mengli Chen. Their work appears in journals such as Bioresource Technology, Journal of Differential Equations, Journal de Mathématiques Pures et Appliquées, Agricultural Water Management and Frontiers in Plant Science.

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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