Mikkel Paltorp

I’m currently a Postdoc in the Section for Scientific Computing at DTU’s Department of Applied Mathematics and Computer Science. My research focuses on leveraging problem structure to develop scalable algorithms. Specifically, I’ve worked on efficient interior point solvers for structured optimization problems in civil engineering. At the moment, I’m exploring structural health monitoring of offshore structures, with a focus on time series classification and transfer learning.

Lately, I’ve become interested in the connections between block tridiagonal matrices, their semiseparable inverses, state-space models, and Gaussian processes.

Previously, I completed my PhD at DTU, working within the Acoustic Technology Group (ACT) and The Centre for Acoustic-Mechanical Micro Systems (CAMM). My research addressed computational challenges in modeling viscous and thermal effects in acoustics using the Boundary Element Method, applying techniques like Hierarchical Matrices, the Fast Multipole Method, and Reduced Order Series Expansions. Parts of this work were done in collaboration with researchers at The Technical University of Munich.