Projects
Interactive Data-Driven Process Simulation for Capacity Management in Healthcare Hasselt University
Providing hospitals with richer insights in their processes: an enhanced methodology for data-driven root-cause analysis using an improved event log Hasselt University
Data-driven models for energy systems and markets: a causal ML approach KU Leuven
Data science tools and data-driven decision-making are being increasingly used in the operation of critical infrastructure such as the electricity and transportation grid. This is driven by the increasing flexibility needs and opportunity arising from proliferation of distributed energy resources such as solar PV, electric vehicles and batteries. However, by definition, many data science tools (e.g. machine learning models) assume a ...
DRIP: Data-driven Control of drip irrigation for sustainable Production in horticulture KU Leuven
General goal: data-driven control of drip irrigation systems offers the best guarantee for sustainable horticulture, in dry years for the future of Flanders. The following goals are set: i) developing a plan for the correct choice and use of soil sensors that monitor the soil moisture status on the plot ii) automatically calibrate the soil moisture simulation with soil water balance models by means of data assimilation, on data generated by ...
Exploring Duality for Future Data-driven Modelling KU Leuven
Future data-driven modelling is increasingly challenging for many systems due to higher complexity levels, such as in energy systems, environmental and climate modelling, traffic and transport, industrial processes, health, safety, and others. This requires powerful concepts and frameworks that enable the design of high quality predictive models. In this proposal E-DUALITY we will explore and engineer the potential of duality principles for ...
Data-driven Modelling and Control of Energy Flexible Residential Loads KU Leuven
Burning fossil fuels to meet humanity's insatiable energy demand is one of the leading drivers for anthropogenic climate change. An important means of mitigating the worst impact of climate change is therefore improving efficiency of current energy use and transitioning to a cleaner energy mix to meet the residual demand. This requires a fundamental rethink of how the energy value-chain is organized at present.
A key technology to ...
Data-Driven Smart Shipping (DDSHIP) Ghent University
In the worldwide R&D on computer-assisted and autonomous navigation the DDSHIP project will contribute by setting a new process flow methodology and test platform for validation and certification through investigations on:
· more accurate and robust perception and situational awareness of the waterborne world around the ship in dense traffic and harsh weather conditions;
· the accurate ...
Part quality optimization through data-driven in-process setpoint control of injection moulding processes. KU Leuven
Designing and producing high performant injection moulded parts is a tedious task, requiring expert knowledge and multiple iterations. One of the key issues is that during the design most often the effect of the production process on the performance of the manufactured part is not accounted for. The injection moulding process may lead to undesired warpage, internal stresses as well as density and mass distributions within the part, which are ...
On real-time solutions for data-driven design, signal processing and control of noisy nonlinear systems KU Leuven
Mathematical models of dynamical processes provide the critical link between real-life applications and techniques for prediction, monitoring, and control. Models are obtained from observed data via system identification methods. These methods, however, do not take into account the subsequent use of the model for design. The issue is currently addressed by trial-and-error human interaction. A rigorous high-gain approach, investigated in this ...