Compressed sensing

Can the compressibility of a signal (such as an image) allow for it to be measured with fewer measurements as one would naively expect? This is indeed the case and the central goal of compressed sensing. ... more later

Ongoing projects

  • Self-certification (with Aditya Kela, David Gross, and Richard Kueng)
    This means to obtain an upper bound on the noise level or reconstruction error together with the reconstruction of the signal.

  • Reconstruction of low-rank tensors

    • Tensor trains (with Željka Stojanac, Daniel Suess, and David Gross)

    • Tensors with low-rank matricizations (with Michał Horodecki)

  • Simultaneously low-rank and sparse matrices (with Peter Jung)