## Educational Background

**2013:**Bachelor’s Degree in Mathematics, Technische Universität Berlin**Oct 2015 - Mar 2016:**Visiting Researcher, University of Cambridge**2016:**Master's Degree in Mathematics, Technische Universität Berlin**since 2016:**PhD student at CCA, University of Cambridge

## Working Experience

**2012-2014:**Student Teaching Assistant, Technische Unversität Berlin**2014-2016:**Student Research Assistant, Technische Unversität Berlin

## Research Interests

- Sampling Theory, Frame Theory, Compressed Sensing, Mathematical Signal Processing, Medical Imaging, Time-Frequency Analysis, Functional and Harmonic Analysis, Machine learning

## Publications

- A.C. Hansen, L. Thesing, On the stable sampling rate for binary measurements and wavelet reconstruction,
*Applied Computational and Harmonic Analysis (2018),*DOI: 10.1016/j.acha.2018.08.004*PDF* - A.C Hansen, L. Terhaar, Sampling from binary measurements - On Reconstructions from Walsh coefficients,
*Proceedings of**the 6th edition of the Signal Processing with Adaptive Sparse Structured Representations workshop 2017 PDF* - A.C. Hansen, L. Thesing, Linear reconstructions and the analysis of the stable sampling rate,
*Sampling Theory in Signal and Image Processing***17**, 103–126, 2018 PDF - R. Calderbank, A. C. Hansen, L. Thesing, B. Roman, On reconstructions from measurements with binary functions,
*Compressed Sensing and Its Applications, Birkhäuser, 97-128, 2019* - L. Thesing, A.C. Hansen, Non-uniform recovery guarantees for binary measurements and infinite-dimensional compressed sensing, arXiv:1909.01143, 2019
*PDF* - L. Thesing, V. Antun, A.C. Hansen, What do AI algorithms actually learn?-On false structures in deep learning, arXiv:1906.01478, 2019
*PDF*

## Publications

On the Stable Sampling rate for binary measurements and wavelet reconstruction

– Applied and Computational Harmonic Analysis

(2020)

48,

630

(DOI: 10.1016/j.acha.2018.08.004)

Sampling from Binary Measurements - on Reconstructions from Walsh Coefficients

– 2017 International Conference on Sampling Theory and Applications (SampTA)

(2017)

256

(DOI: 10.1109/sampta.2017.8024449)

Linear reconstructions and the analysis of the stable sampling rate

– Sampling Theory in Signal and Image Processing