Stefano Castruccio

1.7k total citations
55 papers, 1.1k citations indexed

About

Stefano Castruccio is a scholar working on Global and Planetary Change, Atmospheric Science and Environmental Engineering. According to data from OpenAlex, Stefano Castruccio has authored 55 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Global and Planetary Change, 22 papers in Atmospheric Science and 17 papers in Environmental Engineering. Recurrent topics in Stefano Castruccio's work include Climate variability and models (21 papers), Meteorological Phenomena and Simulations (16 papers) and Wind Energy Research and Development (9 papers). Stefano Castruccio is often cited by papers focused on Climate variability and models (21 papers), Meteorological Phenomena and Simulations (16 papers) and Wind Energy Research and Development (9 papers). Stefano Castruccio collaborates with scholars based in United States, Saudi Arabia and United Kingdom. Stefano Castruccio's co-authors include Marc G. Genton, Paola Crippa, Michael L. Stein, Paolo Giani, Alessandro Anav, Don Howard, Raphaël Huser, Abhinav Thota, Dominick V. Spracklen and Christine Wiedinmyer and has published in prestigious journals such as Journal of the American Statistical Association, Technometrics and Scientific Reports.

In The Last Decade

Stefano Castruccio

51 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Stefano Castruccio United States 18 569 344 329 270 101 55 1.1k
Kamarulzaman Ibrahim Malaysia 20 322 0.6× 264 0.8× 133 0.4× 110 0.4× 83 0.8× 83 1.1k
Andrew Zammit‐Mangion Australia 15 338 0.6× 351 1.0× 339 1.0× 43 0.2× 168 1.7× 66 1.4k
Zhengyuan Zhu United States 23 466 0.8× 626 1.8× 313 1.0× 191 0.7× 150 1.5× 99 1.5k
Bin Guo China 22 373 0.7× 566 1.6× 303 0.9× 605 2.2× 127 1.3× 62 1.4k
Matthias Katzfuß United States 15 405 0.7× 539 1.6× 264 0.8× 47 0.2× 257 2.5× 41 1.5k
William Kleiber United States 19 622 1.1× 531 1.5× 439 1.3× 29 0.1× 211 2.1× 57 1.5k
Zhiqiang Liu China 15 536 0.9× 260 0.8× 163 0.5× 417 1.5× 84 0.8× 53 987
Doug Nychka United States 21 1.2k 2.0× 398 1.2× 853 2.6× 100 0.4× 190 1.9× 38 2.0k
Petra Friederichs Germany 21 1.4k 2.5× 244 0.7× 1.2k 3.5× 33 0.1× 125 1.2× 58 2.1k
Venkataraman Sivakumar South Africa 24 1.1k 2.0× 261 0.8× 1.3k 3.9× 311 1.2× 31 0.3× 121 2.0k

Countries citing papers authored by Stefano Castruccio

Since Specialization
Citations

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

Fields of papers citing papers by Stefano Castruccio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stefano Castruccio

This figure shows the co-authorship network connecting the top 25 collaborators of Stefano Castruccio. A scholar is included among the top collaborators of Stefano Castruccio based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Stefano Castruccio. Stefano Castruccio is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kim, Minwoo, et al.. (2025). Modelling high-resolution spatio-temporal wind with deep echo state networks and stochastic partial differential equations. Journal of the Royal Statistical Society Series C (Applied Statistics). 75(2). 303–319.
2.
Castruccio, Stefano, et al.. (2025). High-resolution urban air quality monitoring from citizen science data with echo-state transformer networks. Journal of the Royal Statistical Society Series C (Applied Statistics). 74(4). 905–924. 1 indexed citations
3.
Datta, Abhirup, Christopher K. Wikle, Edward L. Boone, et al.. (2024). Assessing predictability of environmental time series with statistical and machine learning models. Environmetrics. 36(1). 5 indexed citations
4.
Richter, David H., et al.. (2024). A Physics-Informed, Deep Double Reservoir Network for Forecasting Boundary Layer Velocity. Journal of the American Statistical Association. 120(550). 618–630. 4 indexed citations
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Castruccio, Stefano, et al.. (2023). Uncertainty Reduction and Environmental Justice in Air Pollution Epidemiology: The Importance of Minority Representation. GeoHealth. 7(10). e2023GH000854–e2023GH000854. 2 indexed citations
7.
Zhang, Jiachen, et al.. (2023). High-resolution global precipitation downscaling with latent Gaussian models and non-stationary stochastic partial differential equation structure. Journal of the Royal Statistical Society Series C (Applied Statistics). 73(1). 65–81. 1 indexed citations
8.
Huang, Huang, Stefano Castruccio, Allison H. Baker, & Marc G. Genton. (2023). Saving Storage in Climate Ensembles: A Model-Based Stochastic Approach. Journal of Agricultural Biological and Environmental Statistics. 28(2). 324–344. 4 indexed citations
9.
Wikle, Christopher K., Abhirup Datta, Edward L. Boone, et al.. (2022). An illustration of model agnostic explainability methods applied to environmental data. Environmetrics. 34(1). 12 indexed citations
10.
Shen, Peng, Paola Crippa, & Stefano Castruccio. (2021). Assessing urban mortality from wildfires with a citizen science network. Air Quality Atmosphere & Health. 14(12). 2015–2027. 7 indexed citations
11.
Crippa, Paola, et al.. (2021). A temporal model for vertical extrapolation of wind speed and wind energy assessment. Applied Energy. 301. 117378–117378. 35 indexed citations
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14.
Castruccio, Stefano, et al.. (2020). Marginally parameterized spatio-temporal models and stepwise maximum likelihood estimation. Computational Statistics & Data Analysis. 151. 107018–107018. 6 indexed citations
15.
Castruccio, Stefano, et al.. (2020). Improving Bayesian Local Spatial Models in Large Datasets. Journal of Computational and Graphical Statistics. 30(2). 349–359. 3 indexed citations
16.
Genton, Marc G., et al.. (2020). A high‐resolution bilevel skew‐tstochastic generator for assessing Saudi Arabia's wind energy resources. Environmetrics. 31(7). 10 indexed citations
17.
Castruccio, Stefano, et al.. (2019). Reproducing Internal Variability with Few Ensemble Runs. Journal of Climate. 32(24). 8511–8522. 17 indexed citations
18.
Castruccio, Stefano, et al.. (2018). Current and Future Estimates of Wind Energy Potential Over Saudi Arabia. Journal of Geophysical Research Atmospheres. 123(12). 6443–6459. 37 indexed citations
19.
Castruccio, Stefano, Hernando Ombao, & Marc G. Genton. (2018). A Scalable Multi-Resolution Spatio-Temporal Model for Brain Activation and Connectivity in Fmri Data. Biometrics. 74(3). 823–833. 17 indexed citations
20.
Castruccio, Stefano. (2016). Assessing the spatio-temporal structure of annual and seasonal surface temperature for CMIP5 and reanalysis. Spatial Statistics. 18. 179–193. 8 indexed citations

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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