Zilverling
Guest staff

dr. K. Proksch (Katharina)

Researcher (Guest)
EEMCS-AM-MOR
Zilverling 2098
k.proksch@utwente.nl
+31534899062
Business card

I am a mathematician with main research interests in non-parametric and asymptotic statistics, as well as statistical inverse problems. Of particular interest to me is the development and theoretical investigation of means of statistical inference for applications from the natural sciences. In this context, I have been working on the construction of statistical tests and confidence statements with a recent focus on statistical multiscale analysis and its application to (nanophotonic) imaging and inference on three-dimensional molecular distributions in biological samples. Most of my scientific work has been at the interface of several disciplines, which is what I really love about statistics.

Expertise

  • Mathematics

    • Regression Model
    • Simultaneous Inference
    • Transforms
    • Approximation
    • Convolution
    • Extreme Value Theory
    • Samples
    • Asymptotic Normality

Organisations

Publications

2025

Transfer learning, generative modelling, and nonparametric regression (2025)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Zamolodtchikov, P.https://doi.org/10.3990/1.9789036564649

2024

A two-sample test based on averaged Wilcoxon rank sums over interpoint distances (2024)[Working paper › Preprint]. ArXiv.org. Betken, A., Marjanovic, A. & Proksch, K.https://doi.org/10.48550/arXiv.2408.10570Toward quantitative super-resolution microscopy: molecular maps with statistical guarantees (2024)Microscopy, 73(3), 287-300. Proksch, K., Werner, F., Keller–Findeisen, J., Ta, H. & Munk, A.https://doi.org/10.1093/jmicro/dfad053

2023

Fatigue detection via sequential testing of biomechanical data using martingale statistic (2023)[Working paper › Preprint]. ArXiv.org. Basu, R. & Proksch, K.https://doi.org/10.48550/arXiv.2306.01566

2022

From Small Scales to Large Scales: Distance-to-Measure Density based Geometric Analysis of Complex Data (2022)[Working paper › Working paper]. Proksch, K., Weitkamp, C. A., Staudt, T., Lelandais, B. & Zimmer, C.https://arxiv.org/abs/2205.07689Towards quantitative super-resolution microscopy: Molecular maps with statistical guarantees (2022)[Working paper › Preprint]. Proksch, K., Werner, F., Munk, A., Keller-Findeisen, J. & Ta, H.https://arxiv.org/abs/2207.13426

2021

Two perspectives on high-dimensional estimation problems: posterior contraction and median-of-means (2021)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Finocchio, G.https://doi.org/10.3990/1.9789036552356Nonparametric detection of changes over time in image data from fluorescence microscopy of living cells (2021)Scandinavian journal of statistics, 48(3), 1001-1017. Bissantz, K., Bissantz, N. & Proksch, K.https://doi.org/10.1111/sjos.12517Robust-to-outliers square-root LASSO, simultaneous inference with a MOM approach (2021)[Working paper › Working paper]. ArXiv.org. Finocchio, G., Derumigny, A. & Proksch, K.

2020

Simultaneous inference for Berkson errors-in-variables regression under fixed design (2020)[Working paper › Working paper]. ArXiv.org. Proksch, K., Bissantz, N. & Holzmann, H.https://arxiv.org/abs/2009.00936

Research profiles

Address

University of Twente

Zilverling (building no. 11), room 2098
Hallenweg 19
7522 NH Enschede
Netherlands

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