Dan Leonte
- Postdoctoral Research Fellow, Statistics
About
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 research interests focus primarily on the theory and modeling of temporal and spatial data using trawl processes and ambit fields, as well as inference simulation-based inference methods using deep learning to fit these models efficiently to data.