Projects
The impact of radiotherapy on the human connectome and neurocognitive outcome in pediatric brain tumor patients: towards neuroimaging-guided treatment optimization KU Leuven
For pediatric brain tumor patients, cranial irradiation is known to result in long-term neurocognitive decline. Although radiation-induced neurotoxic mechanisms are hypothesized, the pathophysiology and the extent of neurological damage remains poorly understood. Given the rapidly evolving innovative treatments, optimization of brain tumor treatment requires a good estimation of the extent and dose-dependency of neural damage due to cranial ...
Optimization of overall treatment time for whole gland stereotactic body radiotherapy with integrated focal boosting in prostate cancer KU Leuven
Prostate cancer (PCa) is the most frequently diagnosed cancer in males in Europe and is associated with substantial morbidity and mortality. In this project we aim to make progress in the disease management of PCa in terms of both treatment outcome (tumor control and toxicity outcome) and patient comfort including patients’ quality of life (QoL) during and after treatment. External beam radiotherapy (EBRT) is often used to treat primary PCa. ...
Resistance genotyping for the optimization of anti-HCV treatment. KU Leuven
Chronic hepatitis caused by the hepatitis C virus (HCV) is a serious global health problem. More than 170 million people around the world are currently HCV infected. A minority of patients spontaneously clears the virus, and the remaining with chronic infection are at risk for disease progression potentially leading to liver cancer and death. Although viral clearance can be achieved in a large number of chronically infected patients through ...
Network treatment effect modeling, learning and optimization KU Leuven
Estimates of a treatment effect on an outcome of interest depending on an individual’s characteristics allow optimizing treatment allocation and specification across individuals. Learning a model from data to estimate conditional average treatment effects (CATE) is a challenging task, however, because the effect of a treatment cannot be observed for an individual. As a result, such effects are to be estimated in an indirect manner, requiring ...
Network treatment effect modeling, learning and optimization KU Leuven
Estimates of a treatment effect on an outcome of interest depending on an individual’s characteristics allow optimizing treatment allocation and specification across individuals. Learning a model from data to estimate conditional average treatment effects (CATE) is a challenging task, however, because the effect of a treatment cannot be observed for an individual. As a result, such effects are to be estimated in an indirect manner, requiring ...
Integrated treatment of non-ionic surfactant containing industrial wastewater: process optimization, material selection and life cycle analysis KU Leuven
Endocrine-disrupting compounds are increasingly recognized as a severe threat to aquatic (micro-)organisms and public health. One class of components that have distinct endocrine disruptive properties are non-ionic surfactants, such as alkylphenol ethoxylates (APEOs). Nonyl- and octylphenol ethoxylates are the most well-known APEOs used as non-ionic surfactants and are applied as cleaning, washing and surface-active agents in the textile ...
POSITE: Process optimization with sequential individual treatment effects. University of Antwerp
Process optimization of sulfur-based wastewater treatment Ghent University
Sulfur-based carbon and nitrogen removal from municipal wastewater involves 90% reduction in sludge production, 35% reduction in energy consumption and 35% reduction of CO2 emissions compared to conventional wastewater treatment processes.
This project addresses major challenges limiting full-scale implementation of a sulfur-based process for municipal wastewater treatment. Process optimization will be achieved through steady state ...
Optimization of the aerobic granular sludge process for sustainable wastewater treatment Ghent University
This doctoral research concerns domestic wastewater treatment with aerobic granular sludge, which needs 75% less space 30% less energy compared to conventional systems. The objectives are
- optimization of effluent quality, energy consumption and costs
- application of off-gas analyses for process monitoring and control
- minimization of greenhouse gas emissions
via mathematical modelling, full-scale monitoring and ...