Spatial and spatio-temporal statistics

Dan Leonte

Postdoctoral Research Fellow, Statistics

simulation-based inference neural inference methods Spatial and spatio-temporal statistics ambit fields

Dan obtained his PhD in Mathematics in 2024 from Imperial College London and the University of Oxford, UK, with a thesis titled "Simulation methods, parameter inference and forecasting for trawl processes and ambit fields". He is now a postdoctoral researcher at the King Abdullah University of Science and Technology (KAUST), working in the XSTAT group under Prof. Raphaël Huser's supervision. Education and Early Career Dan obtained his PhD in Mathematics in 2024 from Imperial College London and the University of Oxford, UK. He joined KAUST as a postdoc in April 2025. Research interests Dan's

Paula Moraga

Assistant Professor, Statistics

Spatial and spatio-temporal statistics geospatial modeling Spatial epidemiology Bayesian disease mapping point processes Public health surveillance

Dr. Moraga develops innovative statistical methods and computational tools for geospatial data analysis and health surveillance. The impact of her work has directly informed strategic policy in reducing the burden of diseases such as malaria and cancer in several countries.