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...