- Prof. Aliou Diop, ACE MITIC, LERSTAD, UFR SAT, Université Gaston Berger, Saint- Louis, Sénégal
- Prof. Carlos Ogouyandjou, ACE SMIA, IMSP, Université Abomey-Calavi, Bénin
- Prof. Sophie Dabo-Niang, University of Lille, France and INRIA Lille Nord Europe
Title : Extreme value modeling and Stochastic Analysis on Riemannian manifolds
Project type: Research Project (4 years)
The EVSAR project aims to develop and apply various generative stochastic methods (describing data generation processes), predictive mathematical models (exploratory analyses, estimation of distribution and regression models) to integrate time and space events (spatial or space-time data) massive and complex data (big, functional data, riemannian manifolds). The guiding thread of the research envisaged in this project is the use of stochastic models to represent space and/or time changes driven by real problems in various areas as medicine, biology, epidemiology, physics, environmental, hydrological, natural resources management, renewable energy and agriculture for example to detect, predict, extreme events (floods, natural disasters at different locations) resistance/recurrence of cancer events, epidemic outbreaks, like COVID-19).
- Research themes in digital science: Extreme value index, nonparametric estimation, spatial dependence, Functional data analysis, Riemannian manifolds
- Other research themes and application areas: Environment, Biostatistics, Epidemiology, Finance