Sibo Cheng

67 papers receiving 1.2k citations

Hit Papers

Machine Learning With Data Assimilation and Uncertainty Quantification for Dynamical Systems: A Review 2023 · 127 citations
1270+1+2Years since publication4080120

Peers

Sibo Cheng
Comparison fields: 5 of 136
  • Renewable Energy, Sustainability and the Environment 233
  • Statistical and Nonlinear Physics 175
  • Atmospheric Science 169
  • Global and Planetary Change 171
  • Environmental Engineering 95
Replace Yong Liu with:
Yong Liu China
Hui Liu China
Ling Zhang China
Marco Trapanese Italy
Sen Li China
Howard N. Shapiro United States
W. Rivera Mexico
Gyula Gróf Hungary
Paweł Ocłoń Poland
Sibo Cheng relative to Yong Liu China Yong Liu's profile →
Citations per field
00.5×2.9×
Yong Liu · 1×
Citations per year

Countries citing papers authored by Sibo Cheng

Since Specialization
Citations

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

Fields of papers citing papers by Sibo Cheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015142
2 2016136
3
Machine Learning With Data Assimilation and Uncertainty Quantification for Dynamical Systems: A Review
Hit paper breakdown →
2023127
4 202273
5 202272
6 202255
7 202255
8 202240
9 202240
10 202334
11 201630
12 202330
13 202328
14 201922
15 202322
16 202121
17 202420
18 202219
19 202418
20 202017

About Sibo Cheng

Sibo Cheng is a scholar working on Global and Planetary Change, Atmospheric Science, Computational Mechanics, Statistical and Nonlinear Physics and Aerospace Engineering, having authored 70 papers that have together received 1.3k indexed citations. Recurring topics across this work include Meteorological Phenomena and Simulations (18 papers), Fire effects on ecosystems (10 papers), Climate variability and models (9 papers), Model Reduction and Neural Networks (9 papers), Fluid Dynamics and Turbulent Flows (5 papers), Landslides and related hazards (5 papers), Nuclear Engineering Thermal-Hydraulics (5 papers) and Data Stream Mining Techniques (5 papers). The work is most often cited by research in Renewable Energy, Sustainability and the Environment (233 citations), Statistical and Nonlinear Physics (175 citations), Atmospheric Science (169 citations), Global and Planetary Change (171 citations) and Environmental Engineering (95 citations). Sibo Cheng has collaborated with scholars based in United Kingdom, France and China. Frequent co-authors include Rossella Arcucci, Yike Guo, Helin Gong, Didier Lucor, Paul Chen, Roger Ruan, Dunhui Xiao, César Quilodrán-Casas, Bertrand Iooss and Zhang Chen. Their work appears in journals such as Computer Methods in Applied Mechanics and Engineering, Computer Physics Communications, Environmental Science & Technology, Chemical Engineering Journal and Stochastic Environmental Research and Risk Assessment.

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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