School of Maths and Stats
Newcastle upon Tyne
stefano.castruccio -at- ncl.ac.uk
+44 (0) 191 208 7843
I have been elected as member of the International Statistical Institute (ISI). Also, I won't update this page anymore, my new webpage at the University of Notre Dame should be available from August.
From the next academic year, I will be Assistant Professor at the University of Notre Dame, in the United States.
New manuscript with Felipe Tagle, Paola Crippa and Marc Genton on skew-t models for daily winds in Saudi Arabia in arxiv.
New manuscript with Jaehong Jeong, Paola Crippa and Marc Genton on global wind fields in arxiv.
Our paper "Forecasting Ultrafine Particle Concentrations from Satellite and In-Situ Observations" has been accepted for publication in the Journal of Geophysical Research - Atmospheres. See the link to the publication.
I am organizing a workshop sponsored by the Royal Statistical Society on "Assessing Uncertainty in Premature Mortality Due to Degraded Air Quality", please check this link for information and registration. The event will be held in Newcastle on January, 9th and is free.
Congratulations to PhD students Hollie Johnson and Matthew Edwards, each being awarded an NCAR 2017 Advanced Study Program Fellowship.
I obtained my BSc and MSc in Mathematical Engineering at the Politecnico di Milano in 2005 and 2007 respectively. After a 6 months fellowship at the same institution, I moved to the University of Chicago where I obtained my PhD in Statistics in 2013 under the supervision of Prof. Michael Stein. In 2013 I moved to Saudi Arabia, to King Abdullah University of Science and Technology where I was a Postdoctoral Fellow working with Prof. Marc Genton. Since 2014 I am a Lecturer at Newcastle University.
My main research area is statistical application to climate, and I am particularly interested in the development of statistical models that can act as fast surrogate (emulators) to Earth System Models in a scenario/initial condition ensemble. I am also interested in development of efficient algorithms for fitting very large data set both in the context of Gaussian Processes and of Spatial Extremes.