ongoing master projects TU Delft CGI Estimating congestion and traffic patterns when planning road work Co-Supervisor(s): Leonoor Portengen, Henk van Haaster (CGI) Student: Vosse Meijssen TU Delft Offshore and Dredging Engineering, TU Delft Surrogate models for the characterization of hydrodynamic loads on perforated monopiles Co-Supervisor(s): Oriol Colomés (TU Delft, Offshore Engineering) Student: Ruben Dekeyser TU Delft SNL Domain Decomposition for Machine Learning Based Medical Imaging Co-Supervisor(s): Eric Cyr (Sandia National Laboratories, USA) Student: Corné Verburg TU Delft Otto-von-Guericke University, Max-Planck-Institute of Meteorology Enhancing Sea Ice Dynamics in the Climate System by Machine Learning Co-Supervisor(s): Carolin Mehlmann (Otto-von-Guericke University, Max-Planck-Institute of Meteorology) Student: Brendan Analikwu TU Delft University of Hasselt The Application of Neural Networks to Predict Skin Evolution After Burn Trauma Co-Supervisor(s): Fred Vermolen (University of Hasselt) Student: Selma Husanović open master projects TU Delft Numerical techniques for efficiently solving a nonlinear model for salt intrusion in rivers Co-Supervisor(s): Yoeri Dijkstra (TU Delft, Mathematical Physics) TU Delft COMSOL Improving Nonlinear Solver Convergence Using Machine Learning Co-Supervisor(s): Tycho van Noorden (COMSOL) TU Delft NRG AI-driven turbulence modeling of two-phase flows in nuclear reactors Co-Supervisor(s): Edo Frederix (NRG), Deepesh Toshniwal (TU Delft, Numerical Analysis) TU Delft Error Estimates for Finite Element Simulations Using Neural Networks Co-Supervisor(s): Deepesh Toshniwal (TU Delft, Numerical Analysis) TU Delft Mocean Block Preconditioners for Monolithic Solvers of Very Large Floating Structures Co-Supervisor(s): Oriol Colomés (TU Delft, Offshore Engineering) TU Delft Institute for Marine and Atmospheric Modeling (IMAU) Overlapping Schwarz Domain Decomposition Methods for Implicit Ocean Models Co-Supervisor(s): Jonas Thies (TU Delft, Numerical Analysis) TU Delft Sandia National Laboratories Parallel Multiplicative One-Level Schwarz Preconditioners With FROSch and Trilinos archive master projects TU Delft COMSOL Predicting the Optimal Solver Settings with Machine Learning in COMSOL CFD Module Co-Supervisor(s): Tycho van Noorden (COMSOL) Student: Anouk Zandbergen TU Delft Convolutional Neural Networks for Time-Dependent Fluid Flow Student: Sylle Hoogeveen TU Delft Sioux Technologies Machine Learning for Turbulent Flows Co-Supervisor(s): Werner Lazeroms (Sioux) Student: Elske van Leeuwen TU Delft Domain Decomposition Techniques for the Helmholtz Equation Co-Supervisor(s): Vandana Dwarka (TU Delft, Numerical Analysis) Student: Erik Sieburgh TU Delft Offshore and Dredging Engineering, TU Delft Surrogate models for the characterization of hydrodynamic loads on perforated monopiles Co-Supervisor(s): Oriol Colomés (TU Delft, Offshore Engineering) Student: Quinten Star TU Delft Reduced Order Models for Fluid Flow With Generative Adversarial Networks (GANs) Co-Supervisor(s): Kees Vuik (TU Delft, Numerical Analysis) Student: Mirko Kemna