Jun Cheng

2.4k citations
63 papers · 1.8k · h-index 20

Impact in

Papers in

Jun Cheng

62 papers receiving 1.8k citations

Peers

Jun Cheng
Comparison fields: 5 of 138
  • Aging 61
  • Modeling and Simulation 128
  • Cell Biology 422
  • Safety, Risk, Reliability and Quality 156
  • Molecular Biology 857
Replace José J. Muñoz with:
José J. Muñoz Spain
Jiyang Yu United States
Hong Yan Duan China
Weiming Tian China
Alessandra Bonfanti United Kingdom
Ge Yang China
Uri Gat Israel
Qizhi Xie China
M. Philippe France
Chaoyi Li China
Jun Cheng relative to José J. Muñoz Spain José J. Muñoz's profile →
Citations per field
00.5×2×4×5.5×
José J. Muñoz · 1×
Citations per year

Countries citing papers authored by Jun Cheng

Since Specialization
Citations

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

Fields of papers citing papers by Jun Cheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002309
2 2008277
3 2007145
4 2008102
5 201172
6 202066
7 201859
8 200956
9 201953
10 202051
11 200550
12 201142
13 201141
14 200941
15 202037
16 201932
17 200932
18 201326
19 201320
20 201120

About Jun Cheng

Jun Cheng is a scholar working on Cell Biology, Safety, Risk, Reliability and Quality, Aerospace Engineering, Statistics, Probability and Uncertainty and Computational Mechanics, having authored 63 papers that have together received 1.8k indexed citations. Recurring topics across this work include Combustion and Detonation Processes (9 papers), Microtubule and mitosis dynamics (8 papers), Fire dynamics and safety research (7 papers), Electrospun Nanofibers in Biomedical Applications (4 papers), Nanofluid Flow and Heat Transfer (4 papers), Developmental Biology and Gene Regulation (4 papers), Gear and Bearing Dynamics Analysis (4 papers) and Tribology and Lubrication Engineering (4 papers). The work is most often cited by research in Aging (61 citations), Modeling and Simulation (128 citations), Cell Biology (422 citations), Safety, Risk, Reliability and Quality (156 citations) and Molecular Biology (857 citations). Jun Cheng has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Alan J. Hunt, Yukiko M Yamashita, Shijun Liao, Bo Zhang, Nahid Hemati, Nezaket Türkel, Margaret T. Fuller, Fuxing Wang, Henry T. Schek and David J. Odde. Their work appears in journals such as Aerospace Science and Technology, Fuel, Advanced Healthcare Materials, Current Biology and Combustion and Flame.

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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