open master projects TU Delft TU Berlin Machine Learning-Accelerated Solvers for Computational Fluid Dynamics Simulations Co-Supervisor(s): Merten Stender (TU Berlin) TU Delft Leiden University Geometry Learning for Complex Shaped Cells Co-Supervisor(s): Qiyao Peng (Leiden University) TU Delft Domain Decomposition Techniques for the Helmholtz Equation - HPC Implementation Co-Supervisor(s): Vandana Dwarka (TU Delft, Numerical Analysis) TU Delft Domain Decomposition Techniques for the Helmholtz Equation - Theoretical Investigation Co-Supervisor(s): Vandana Dwarka (TU Delft, Numerical Analysis) 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 Error Estimates for Finite Element Simulations Using Neural Networks Co-Supervisor(s): Deepesh Toshniwal (TU Delft, Numerical Analysis) 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 ongoing master projects TU Delft ASML Data-driven methods for machine-induced metrology errors Co-Supervisor(s): Sjoerd Wiarda (ASML) Student: Michael Aldorf TU Delft ASML Creating a machine learning based outlier removal algorithm that incorporates a priori knowledge of the physics Co-Supervisor(s): Lucas Bekker (ASML) Student: Thomas Kamminga TU Delft Brown University, Università della Svizzera italiana Decomposing Graph Neural Networks Co-Supervisor(s): Alena Kopaničáková (Brown University, Università della Svizzera italiana) Student: Mirte van Loenen TU Delft TU Braunschweig Separating longtime behavior and learning of mechanisms Co-Supervisor(s): Cordula Reisch (TU Braunschweig) Student: Tirtho Sarathi Saha 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) Student: Gonzalo Bonilla Moreno 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 TU Delft Mocean Block Preconditioners for Monolithic Solvers of Very Large Floating Structures Co-Supervisor(s): Oriol Colomés (TU Delft, Offshore Engineering) Student: Shreyas Prashanth archive master projects TU Delft Deltares Machine learning for post-storm profile predictions Co-Supervisor(s): José Antonio Álvarez Antolínez, Ad Reniers (TU Delft, Hydraulic Engineering), Panos Athanasiou, and Robert McCall (Deltares) Student: Koen van Asselt 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 Sandia National Laboratories Domain Decomposition for Machine Learning Based Medical Imaging Co-Supervisor(s): Eric Cyr (Sandia National Laboratories, USA) Student: Corné Verburg 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