Modélisation de valeurs extrêmes pour l'analyse de la pandémie de COVID-19 et de son impact et l'atténuation des futures crises connexes [Translation: Modelling extreme values for the analysis of the COVID-19 pandemic and its impact, and mitigation of related crises]

Risk inference and prediction is of critical importance - to policy makers, finance and insurance companies, and society. They are particularly important in environments going through highly disruptive and generally unprecedented events, such as the current double shock of the COVID-19 pandemic and falling oil prices, but also for climate change and associated extreme weather episodes. . There are few statistical techniques available to analyze extreme events in such a non-stationary and time-constrained world, and they generally have limited applicability. Dr Gilles Stupfler, winner of an AXA Research Fund Award at ENSAI, seeks to push the boundaries of current knowledge by tackling this problem. His research project aims to improve the collection and quality of data in the field of health by developing theoretical and applied tools. His research will provide a combination of new techniques for measuring risks and high-dimensional data methods to create a diverse toolbox for the assessment and mitigation of extreme risks due to rare events, including a pandemic or other disruptive events.