Projects
PHD POSITION IN DATA ANALYTICS AND STATISTICAL MODELING KU Leuven
In many research fields data dimension reduction techniques are widely used. Fields such as chemometrics, signal processing, and video compression, try to deal with these issues with tools that transform high-dimensional data to lower dimensions where the meaningful properties of the data are retained. Principal Component Analysis (PCA) is a widely used tool for dimension reduction. However, it is known that PCA is not robust against ...
SHASIZE: a predictive tool based on statistical shape modeling for accurate clothing size prediction. University of Antwerp
Statistical challenges in modeling longitudinal dyadic data. Ghent University
Researchers studying longitudinal data from couples to assess the interpersonal interaction may be faced with several statistical challenges. What is the most appropriate modeling technique? How can one deal with categorical outcomes or missing data? How can one perform a mediation analysis in such setting? This project aims to provide appropriate and innovative answers to those questions.
Statistical Analysis and Modeling of Selectorless Non-filamentary Resistive RAM KU Leuven
Resistive switching memories are a class of emerging memories competing in several application domains, for example, Storage Class Memories and Internet of Things. Back-end-of-line compatible fabrication with possibility of stacking and scaling these devices make them attractive for high density applications. However, integrating these memory cells in an array leads to sneak path issues. A selector or access element can overcome this ...
Statistical Modeling and Estimation of Simultaneous Degradations in Digital Images Ghent University
In digital still camera and medical imaging devices there is a trend to increase the image resolution, to use shorter acquisition times and lower radiation doses. This causes many challenges for the processing techniques in the devices. In this project, we will develop statistical models and estimation techniques for multiple simultaneous degradations in images, in order to further improve existing image reconstruction techniques. We ...
Statistical modeling of image processing methods in medical imaging Ghent University
The main theme will be to model the total diagnostic image processing chain, so that weak or critical points in algorithms can be identified and improved already in early stages of research. Specifically the models will allow estimating the robustness of a combination of a cascade of image processing and analysis operaters w.r.t. image nois, suboptimal parameter setting etc. To ensure that the methodology will eventually be applicable in ...