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Current PhD projects
Scientific Computing
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Algorithms, Logic and Graphs
Cognitive Systems
Cybersecurity Engineering
Dynamical Systems
Embedded Systems Engineering
Formal Methods
Mathematics
Scientific Computing
Aksel Kaastrup Rasmussen
Anders Dalsgaard Melander
Anders Hilmar Damm Andersen
Andreas Horst
Jasper Marijn Everink
Jens Visbech
Laura Hjort Blicher
Lujing Chen
Rafael Flock
Asbjørn Thode Reenberg
Frederik Hagsholm Pedersen
Hjørdis Amanda Schlüter
Katrine Ottesen Bangsgaard
Kristoffer Linder-Steinlein
Marcus Krogh Nielsen
Morten Ryberg Wahlgreen
Puyuan Mi
Sabine Fie Hansen
Sarah Ellinor Engell
Silja Westphal Christensen
Zhanhao Zhang
Software and Process Engineering
Software Systems Engineering
Statistics and Data Analysis
Visual Computing
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PhD projects affiliated with DTU Compute
Current PhD projects in Scientific Computing
Computational Uncertainty Quantification of Hybrid Inverse Problems
Aksel Kaastrup Rasmussen: Seeing inside an object without opening it and be certain of what you see
High-Performance Computing for Computational Fluid Dynamics for Free
Anders Dalsgaard Melander: High-Performance Computing for Computational Fluid Dynamics for Free Surface Flows
Digitalization in the form of simulation, control, and optimization is a key enabler...
New prior methods for better solutions of inverse problems
Computational Uncertainty Quantification for Inverse Problems with Implicit Priors
Jasper Marijn Everink: Different assumptions on uncertainty might give different conclusions
Wave energy – the world’s largest untapped source of energy
The bigger picture of lipid metabolism
Approximation methods for optimization with rank structure
Lujing Chen: Searching for structure: faster methods for system identification
Dimensionality Challenges in UQ for Inverse Problems
Rafael Flock: Shrinking large dimensional Bayesian inverse problems
Systematic Mathematical Modeling for Agile Development of Model Based Medical...
Asbjørn Thode Reenberg: Automated Medical Treatment Improves the Quality of Life for Patients Today, many people suffer from diseases that require constant treatment...
Computational Methods for Optimization with Rank Structure
Frederik Hagsholm Pedersen: Identifying and exploiting hidden structure for efficient optimization in data science
Conductivity reconstruction on Riemannian manifolds from power density measurements...
Hjørdis Amanda Schlüter: How to study the interior electrical conductivity of a body from the outside?
Prior Modeling for Computational UQ for Inverse Problems
Katrine Ottesen Bangsgaard: Quantifying the eliability of computed tomography and inverse problems in general
Uncertainty Quantification for Source Localization and Passive Imaging in Random...
Kristoffer Linder-Steinlein: Passive imaging and inverse problems in random media
Economic Optimizing Control for a U-loop Reactor
Marcus Krogh Nielsen: Sustainable protein production for a growing population
Economic Nonlinear Model Predictive Control for Integrated and Optimized Non-Stationary...
Morten Ryberg Wahlgreen: Optimal operation of biotechnological processes for improved peptide and vaccine production
Model Error Reduction in Inverse Problems
Puyuan Mi: How to reduce the error introduced when modelling an inverse problem?
Robust Surrogate Modelling for Antenna Design Applications
Sabine Fie Hansen: Paving the Road for Faster Antenna Design Analysis
Model-Based Algorithm for Regimen Identification in Treatment of T2D
Sarah Ellinor Engell: Fast and Affordable Optimization of Insulin Treatment. Data from Artificial Pancreas systems may hold the key to reaching treatment goals...
Uncertainty Quantification for Tomographic Reconstruction
Silja Westphal Christensen: How much can we trust tomographic reconstructions?
Economic Model Predictive Control for Zero-Emission Industrial Processes
Zhanhao Zhang: An Economic Model Predictive Control Based Advanced Process Control System Could Reduce Oil Concentration of Discharged Water for Oil and Gas Production...
Updated on 24 May 2022
Updated on 24 May 2022