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mipals/README.md

Hi there ๐Ÿ‘‹

I am currently doing a 1-year PostDoc at the Section for Scientific Computing at the Technical University of Denmark. Here I look into efficient implementations of interior-point methods for a certain applications in civil engineering. Previously I was a PhD student in the Acoustic Technology Group (ACT) as well as The Centre for Acoustic-Mechanical Micro Systems (CAMM). Before this I studied computational science and engineering with an emphasis on optimization methods and numerical analysis. In particular I took an interest in rank structured approaches which lead me down the path of studying Boundary Integral Equations applied to acoustics.

Things I deal with on a regular basis

  • Boundary Integral Equations (and their solution through the Boundary Element Method using Fast Multipole Methods and $\mathcal{H}$-matrices).
  • Structured linear algebra (specifically rank structure and sparsity).
  • Optimization algorithms (mostly interior point methods).

Pinned

  1. BoundaryIntegralEquations.jl BoundaryIntegralEquations.jl Public

    A simple package for solving Boundary Integral Equations using the (collocation) Boundary Element Method.

    Julia 9

  2. FMM2D.jl FMM2D.jl Public

    A Julia interface to the FMM2D library from the Flatiron Institute

    Julia 3

  3. BlockDiagonalMatrices.jl BlockDiagonalMatrices.jl Public

    A Julia package for computing with block diagonal matrices

    Julia

  4. SymSemiseparableMatrices.jl SymSemiseparableMatrices.jl Public

    A package for efficiently computing with symmetric extended generator representable semiseparable matrices (a type of rank structured matrix).

    Julia 1

  5. egrssmatrices egrssmatrices Public

    Short implementation of a EGRSS matrix format including an application example in smoothing spline fitting.

    Python 2

  6. GeneralizedSmoothingSplines.jl GeneralizedSmoothingSplines.jl Public

    A package for fitting (curve restricted) smoothing splines of degrees 2p-1 using the Gaussian process view with a rank structured kernel matrix.

    Julia 3