Discipline codes:Statistics (01010703), Probability theory (01010702)
Supervised PhDs
Towards a statistical and mathematical framework for the analysis of infectious disease data from a spatial, temporal and survival analysis point of view
Njeri Kamau for the title Doctor of Sciences: Statistics (doctorate in progress)
Supervised as Copromotor
Het schatten van de cross-ratio functie met Bernstein veeltermen
Ömer Sercik for the title Doctor of Sciences: Statistics (doctorate in progress)
Supervised as Copromotor
Nonparametric estimation of time-varying association measures with censored data
Marsha Salsabilla Nugroho for the title Doctor of Sciences: Statistics (doctorate in progress)
Supervised as Copromotor
Statistical methods to estimate infectious disease parameters and individual heterogeneity
Adelino Martins for the title Doctor of Sciences: Statistics in 2022
Supervised as Promotor
On the sero-epidemiology of measles in Belgium: on immunogenicity and persistence of vaccination and immunity gaps
Julie Schenk for the title Doctor of Sciences: Statistics in 2022
Public health decision making with stochastic individual-based models: a translational framework driven by advances in health economics, model inference and reinforcement learning (ACCELERATE) (Research)
01/01/2023 - 31/12/2026
Efficient and rapidly SCAlable EU-wide evidence-driven Pandemic response plans through dynamic Epidemic data assimilation (Research)
01/01/2023 - 31/12/2026
Bernstein-based estimation of the cross-ratio function (Research)
01/01/2022 - 31/12/2025
Solar Cookers for All (Education)
01/09/2023 - 31/08/2025
Nonparametric estimation of time-varying association measures for bivariate censored time-to-event data (Research)
01/10/2020 - 30/09/2024
Statistics for development in Indonesia (Education)
01/01/2019 - 31/08/2022
DSI COVID-19 team (Research)
15/06/2020 - 14/06/2022
Statistical methods to estimate infectious disease parameters and individual heterogeneity using multivariate serological data (Research)
01/07/2017 - 31/12/2021
RESTORE: REalistic forecaSTing, cOntrol and pREparedness for coming COVID-19 waves (Research)