Publications

Biography

I received my PhD degree from Chalmers University of Technology in 2004. After graduating from Chalmers, I worked for two years as a Research Assistant Professor at the Toyota Technological Institute in Chicago.

Since 2006, I work as a Research Scientist at Simula Research Laboratory and hold a part-time position (20%) as Associate Professor at the University of Oslo.

I am head of the Automated and Distributed Computing research group. I also manage the YFF (Young Outstanding Investigator) project Automation of Error Control with Application to Fluid-Structure Interaction in Biomedicine.

Automated Computing

My main research interest is Automated Computing. The writing of scientific software is often both tedious and error-prone, leading to long development cycles and unreliable software. To further complicate matters, development of efficient scientific software requires specialization, both to the hardware and the application at and. However, manual labor may in many cases be replaced by automated code generation, ultimately leading to automated development of efficient scientific software.

Code generation is the key to automated computing and forms the basis for the FEniCS project. The FEniCS project was initiated in 2003 aiming at a complete Automation of Computational Mathematical Modeling (ACMM), including the automation of discretization, discrete solution, error control, modeling and optimization. Initially a collaboration between researchers at Chalmers University of Technology and the University of Chicago, the FEniCS project has grown to include collaborators from the University of Chicago, Argonne National Laboratory, Delft University of Technology, Royal Institute of Technology KTH, Simula Research Laboratory, Texas Tech University and University of Cambridge (in order of appearance).

As part of the FEniCS project, I have developed FFC, the FEniCS Form Compiler. FFC automates the generation of efficient code for finite element computing, based on a high-level description of a variational problem in near mathematical notation. I am also one of the main developers of DOLFIN, the C++/Python interface to  FEniCS, and UFC, an interface for automated code generation.

Adaptive Finite Element Methods

As part of my thesis work, I developed a new class of multi-adaptive Galerkin finite element methods for the solution of time-dependent ordinary and partial differential equations. Multi-adaptive methods allow the use of individual time step sequences for different components of a system. In particular, this allows the use of small time steps in one region of a domain and large time steps in other regions to improve the accuracy and/or efficiency of the solution of time-dependent problems.

I am currently investigating efficient adaptive methods for fluid flow and fluid–structure interaction, with a particular focus on biomedical flow problems posed on complex geometries.  I am also working on extending the ideas of automated computing to the implementation of adaptive finite element methods. The goal is ultimately to automate the generation of adaptive algorithms with a guaranteed control of the accuracy of computed solutions, based on automated generation of dual problems and a posteriori error estimates.