Current Position

Associate Professor, Department of Applied and Computational Mathematics and Statistics

Education

Ph.D., University of Chicago
M.S., Politecnico di Milano, Italy
B.S., Politecnico di Milano, Italy

Research Interests

Prof. Castruccio’s main area of research focuses on the development of spatio-temporal statistical models for environmental applications, with applications spanning from assessment of renewable energy resources to assessing mortality from air pollution. His focus is mostly on climate and weather modes, and the use of statistical models that can act as a stochastic approximation to provide a computationally affordable assessment of parameter sensitivity analysis. 

Key Words

Wind Energy, Data Science, Machine Learning, Big Data, Climate Models, Spatio-Temporal Data, Visualization of Uncertainty in Space and Time

Relevant Energy Publications

1. Chen, Wanfang, Stefano Castruccio, and Marc G. Genton. "Assessing the risk of disruption of wind turbine operations in Saudi Arabia using Bayesian spatial extremes." Extremes 24, no. 2 (2021): 267-292.
2. Tagle, Felipe, Stefano Castruccio, Paola Crippa, and Marc G. Genton. "A non‐Gaussian spatio‐temporal model for daily wind speeds based on a multi‐variate skew‐t distribution." Journal of Time Series Analysis 40, no. 3 (2019): 312-326.
3. Jeong, Jaehong, Yuan Yan, Stefano Castruccio, and Marc G. Genton. "A stochastic generator of global monthly wind energy with Tukey g-and-h autoregressive processes." Statistica Sinica 29, no. 3 (2019): 1105-1126.
4. Jeong, Jaehong, Stefano Castruccio, Paola Crippa, and Marc G. Genton. "Reducing storage of global wind ensembles with stochastic generators." The Annals of Applied Statistics 12, no. 1 (2018): 490-509.
5. Chen, Wanfang, Stefano Castruccio, Marc G. Genton, and Paola Crippa. "Current and future estimates of wind energy potential over Saudi Arabia." Journal of Geophysical Research: Atmospheres 123, no. 12 (2018): 6443-6459.

 

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