About Me
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
# Estimator
# Ill-Posed Problem
# Inverse Model
# Inverse Regression
# Radon Transform
# Regression Function
# Regularization Parameter
# Simultaneous Inference
Organisations
Publications
Recent
Proksch, K., Werner, F., Munk, A., Keller-Findeisen, J., & Ta, H. (2022).
Towards quantitative super-resolution microscopy: Molecular maps with statistical guarantees.
https://arxiv.org/abs/2207.13426
Proksch, K., Weitkamp, C. A., Staudt, T., Lelandais, B., & Zimmer, C. (2022).
From Small Scales to Large Scales: Distance-to-Measure Density based Geometric Analysis of Complex Data.
https://arxiv.org/abs/2205.07689
Finocchio, G. (2021).
Two perspectives on high-dimensional estimation problems: posterior contraction and median-of-means. [PhD Thesis - Research UT, graduation UT, University of Twente]. University of Twente.
https://doi.org/10.3990/1.9789036552356
Bissantz, K., Bissantz, N.
, & Proksch, K. (2021).
Nonparametric detection of changes over time in image data from fluorescence microscopy of living cells.
Scandinavian journal of statistics,
48(3), 1001-1017. Advance online publication.
https://doi.org/10.1111/sjos.12517
Finocchio, G.
, Derumigny, A.
, & Proksch, K. (2021).
Robust-to-outliers square-root LASSO, simultaneous inference with a MOM approach. ArXiv.org.
Munk, A.
, Proksch, K., Li, H., & Werner, F. (2020).
Photonic imaging with statistical guarantees: From multiscale testing to multiscale estimation. In
Topics in Applied Physics (pp. 283-312). (Topics in Applied Physics; Vol. 134). Springer.
https://doi.org/10.1007/978-3-030-34413-9_11
Proksch, K., Bissantz, N., & Holzmann, H. (2020).
Simultaneous inference for Berkson errors-in-variables regression under fixed design. ArXiv.org.
https://arxiv.org/abs/2009.00936
Weitkamp, C. A.
, Proksch, K., Tameling, C., & Munk, A. (2020).
Gromov-Wasserstein Distance based Object Matching: Asymptotic Inference. ArXiv.org.
https://arxiv.org/abs/2006.12287
Dunker, F., Eckle, K.
, Proksch, K., & Schmidt-Hieber, A. J. (2019).
Tests for qualitative features in the random coefficients model.
Electronic Journal of Statistics,
13(2), 2257-2306.
https://doi.org/10.1214/19-EJS1570
Eckle, K., Bissantz, N., Dette, H.
, Proksch, K., & Einecke, S. (2018).
Multiscale inference for a multivariate density with applications to X-ray astronomy.
Annals of the Institute of Statistical Mathematics,
70(3), 647-689. Advance online publication.
https://doi.org/10.1007/s10463-017-0605-1
UT Research Information System
Courses Academic Year 2023/2024
Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.
Courses Academic Year 2022/2023
Contact Details
Visiting Address
University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
(building no. 11), room 2098
Hallenweg 19
7522NH Enschede
The Netherlands
Mailing Address
University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
2098
P.O. Box 217
7500 AE Enschede
The Netherlands