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Alice Corbella is an Assistant Professor in Applied Statistics at the University of Warwick, where she focuses on developing advanced methods to tackle health problems, particularly in relation to infectious disease dynamics. Previously, she was a Post-Doctoral Research Associate as part of the Bayes4Health collaboration, conducting research into Markov Chain Monte Carlo (MCMC) methods and their applications in Bayesian inference. Alice completed her PhD at the MRC Biostatistics Unit in Cambridge, specializing in epidemic models for influenza, under the supervision of Anne Presanis and Dani De Angelis. Her work includes a variety of statistical methodologies and collaborations across several studies related to COVID-19 and seasonal influenza, aiming at estimating disease transmission and public health impacts. She has published multiple articles in esteemed journals, contributing to the understanding and modeling of epidemic data.
Includes General, Mechanical, Civil, Electrical, Biomedical, and Manufacturing Engineering. Most programs fall under English Band A.