Projects
Three essays on structural parameter estimation and bias correction for discrete choice models. KU Leuven
In the last few decades, we have observed a growing body of economic research that focuses on structural economic models. Several authors, including Dubé et al. (2005), Reis and Wolak (2007), Keane et al. (2011), Low and Meghir (2017), highlight the importance of structural models in providing researchers with better insights on behaviors of economic agents, which cannot be captured by descriptive econometric models. The three main ...
Model-based distributed sensor fusion for MAGV state and parameter estimation KU Leuven
The proposed research deals with indirect methods utilizing the standard set of sensors to estimate or observe vehicle state and/or parameters. Novel model-based approaches will be developed for fusing distributed sensor information with the aim of obtaining online vehicle state and/or parameter estimates. The MAGV (Multi-Actuated Ground Vehicle) subsystems for the estimation purposes will be presented in the form of advanced mechatronic ...
Parameter estimation and real-time prediction of Dengue outbreaks using model averaging Hasselt University
Experimental model based estimation of inputs and parameters for vibro-acoustic system-level predictions KU Leuven
Statistical methods for the estimation of age- and time-dependent epidemiological malaria parameters and the analysis of social network data as a novel approach to design malaria elimination strategies. University of Antwerp
Estimation of the infection disease parameters based on mixture models. Hasselt University
Optimal estimation of nuisance paramters and models in causal inference Ghent University
Inferring cause-effect relationships is often hindered by the presence of confounders. Hence, we need to build statistical models to adjust for these confounders. However, these models are not of scientific interest. This project focuses on optimal estimation of nuisance parameters indexing these models and the optimal choice of these nuisance models, both by minimizing the MSE of the causal effect.
Estimation of soil physical paramters through remote sensing and hydrologica modelling Ghent University
Remotely sensed soil moisture values will be calculated using multitemporal (weekly) and multifrequency (L, C and X bands) radardata, through which information about the soil moisture profile is available. This information will be used in a hydrologica model in order to invert the soil physical properties which lead to this profile. This will be performed using a Kalman filter.