Rossella Arcucci

79 papers receiving 1.5k citations

Rossella Arcucci's Hit Papers

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

Peers

Rossella Arcucci
Comparison fields: 5 of 126
  • Atmospheric Science 449
  • Statistical and Nonlinear Physics 301
  • Environmental Engineering 246
  • Global and Planetary Change 302
  • Computational Mechanics 203
Replace Xiaowei Jia with:
Xiaowei Jia United States
Rémi Lam United States
Joseph H. W. Lee Hong Kong
Fei Hu China
Davidson Martins Moreira Brazil
Bertrand Iooss France
Ribana Roscher Germany
Jared Willard United States
Rohitash Chandra Australia
Wenyuan Liao Canada
Rossella Arcucci relative to Xiaowei Jia United States Xiaowei Jia's profile →
Citations per field
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Xiaowei Jia · 1×
Citations per year

Countries citing papers authored by Rossella Arcucci

Since Specialization
Citations

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

Fields of papers citing papers by Rossella Arcucci

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 87 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Machine Learning With Data Assimilation and Uncertainty Quantification for Dynamical Systems: A Review
Hit paper breakdown →
2023127
2 2019100
3 202183
4 202176
5 202272
6 202069
7 202255
8 202054
9 202244
10 201844
11 202240
12 202240
13 202038
14 202236
15 202334
16 202032
17 202330
18 202027
19 201727
20 202023

About Rossella Arcucci

Rossella Arcucci is a scholar working on Atmospheric Science, Global and Planetary Change, Artificial Intelligence, Environmental Engineering and Statistical and Nonlinear Physics, having authored 87 papers that have together received 1.5k indexed citations. Recurring topics across this work include Meteorological Phenomena and Simulations (35 papers), Climate variability and models (12 papers), Model Reduction and Neural Networks (11 papers), Wind and Air Flow Studies (10 papers), Fire effects on ecosystems (8 papers), Innovative Microfluidic and Catalytic Techniques Innovation (5 papers), Oceanographic and Atmospheric Processes (5 papers) and Data Stream Mining Techniques (5 papers). The work is most often cited by research in Atmospheric Science (449 citations), Statistical and Nonlinear Physics (301 citations), Environmental Engineering (246 citations), Global and Planetary Change (302 citations) and Computational Mechanics (203 citations). Rossella Arcucci has collaborated with scholars based in United Kingdom, Italy and China. Frequent co-authors include Yike Guo, Sibo Cheng, Christopher C. Pain, Luisa D’Amore, César Quilodrán-Casas, Pin Wu, Miguel Molina-Solana, Dunhui Xiao, Jiangcheng Zhu and Omar K. Matar. Their work appears in journals such as Computer Methods in Applied Mechanics and Engineering, Journal of Computational Science, Journal of Computational Physics, Computer Physics Communications and Journal of 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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