Mikkel Paltorp

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linkedin: Mikkel Paltorp
scholar: Mikkel Paltorp
github: mipals
email: mikkel.paltorp@gmail.com
orcid: 0000-0002-4274-2614

I completed my PhD at the Technical University of Denmark (DTU), working within the Acoustic Technology (ACT) group 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 such as hierarchical matrices (-matrices), the Fast Multipole Method (FMM), and Reduced Order Series Expansions. Part of this work were done in collaboration with researchers at The Technical University of Munich (TUM).

I’m currently a Postdoc in the Section for Scientific Computing at DTU’s Department of Applied Mathematics and Computer Science. My current research focuses on leveraging problem structure to develop scalable algorithms. Previously, I worked on efficient interior point algorithms for finite element limit analysis problems in civil engineering.

Experience

• PostDoc, Section for Scientific Computing, DTU Compute (2024 - Present).
• PhD, Acoustic Technology & CAMM, DTU Electro (2020 - 2024).

Education

• M.Sc.Eng in Mathematical Modelling and Computation (2020).
• B.Sc.Eng in Mathematics and Technology (2017).
• Exchange semester - McGill University (2016).

Activities

• Active member of the Julia user group of Copenhagen since 2021.¹¹ I organize events. Our events have around 30 participants and have included speakers from Novonesis, PFA, PumasAI, and MIT.
• Not-so-active member of Nørrebro Klatreklub since 2019.

Technical Skills

• Programming: Julia, Python, MATLAB, R, C, Rust
• Tools: Git, LaTeX, Typst, macOS, Linux, CI/CD, uv, JuMP, Jupyter, Pluto, Jax

Scientific Skills

• Numerical Linear Algebra (Sparsity, rank-structure, hierarchical matrices, etc.)
• Scientific Computing (Element Methods (FEM/BEM), Adjoint Methods, etc.)
• Machine Learning (Gaussian Processes, Deep Learning, Numerical Linear Algebra, etc.)
• Optimization (Interior Point Methods, Semidefinite Programming, etc.)