Projects
DISCO-Func: Discrete Optimization in Neural Network Function Classes through Submodular Analysis KU Leuven
Driven by advances in deep learning, powerful automated algorithms enable us to hold conversations with virtual assistants running on our mobile phone, cars are autonomously driving on streets in mixed traffic, increasingly sophisticated medical diagnostic software is assisting doctors in making life-saving decisions, and social networks and media libraries are automatically indexed and personalized to individual users. At the core of these ...
Generation of a human interactome network using MAPPIT Ghent University
Protein-protein interactions are crucial for virtually all biological processes. Detailed interaction networks can provide novel insights in the normal and pathological functions of a given protein. Analysis of the human interactome is done using the yeast two-hybrid technique, whereby the accuracy is sometimes questioned. We will contribute to these large-scales programs by asystematic analysis of observed interactions using MAPPIT.
DAEMON: Deep polymer network design through Algorithm EnhanceMents, OptimizatioNs and machine learning Ghent University
The use of polymers, both synthetic and natural, is ubiquitous and they are found in virtually any aspect of modern life, including e.g. engineering composites, medical devices, packaging, and electronics. Several topologies can derive from the different types of connectivities and 3D positioning of all the bonds inside polymers, which are the base to predict the polymer macroscopic properties. A particularly complex case are the ...
Multimodal and computational framework of cerebral network organization to test different hypotheses for the emergence of consciousness Ghent University
The majority of studies considering patients with disorders of consciousness (DOC) are observational. The present project aims to test the hypotheses for the emergence of consciousness by studying cerebral dysfunction in pathological states of consciousness on a mechanistic level. This will be achieved through multimodal neuroimaging/ neurophysiology and a biophysical modelling framework. The studies will comprise behavioral, electrical (EEG) ...
Modelling protein network effects of mutations and post-translational modifications in yeast KU Leuven
The aim of this thesis is to contribute to better understanding of essential molecular mechanisms in yeast Saccharomyces cerevisiae cells. Two main research questions are addressed: i. how do post-translational modifications (PTMs) affect yeast protein-protein interactions, and ii. what are the mechanisms underlying yeast ethanol tolerance.
Post-translational modifications, such as the addition of chemical moieties on specific ...
Architecture and algorithms for efficient management of virtualized ICN Networks Ghent University
Over the last decades, the Internet has evolved from a research network connecting a couple of hundred nodes to a system connecting billions of users around the globe. This astonishing evolution has been driven by a continuous innovation, both in terms of technology, service offering and user requirements. While in the early days the Internet was mainly used for static services such as e-mail and web browsing, a wide variety of rich services ...
Robust and energy-efficient virtual sensor networks. University of Antwerp
Output Filters for Grid-Tied Converters: Component Sizing, Controller Co-Design and Winding-Loss Analysis KU Leuven
There has been a high increase in demand for high-performance output filters for power converters, possessing high attenuation and high bandwidth. Many emerging applications require high bandwidth and low output distortion, e.g. controllable power sources and grid-tied converters. Moreover, at high switching frequency, the filter attenuation needs to comply with the electromagnetic interference (EMI) standard, which is more stringent than the ...
Algorithms for Efficient Management of Large-Scale Virtualized Networks by means of Advanced Learning and Reasoning Techniques Ghent University
The promising concept of geometric routing in large scale telecommunication networks will be extended to accommodate simultaneous embedding construction and dynamic assignment of virtual network functions. This requires extensive research into novel methods that tightly integrate learning and reasoning, using current and historical network and traffic information and capturing network dynamics via temporal dependencies.