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New R packages

during the spring we published several new R packages on CRAN. KernelICA gives an implementation of kernel ICA, and ssaBSS has several methods for (non-)stationary source separation. shapeNA allows for robust shape estimation when there are missing values in the data.

Meanwhile I am involved in 22 packages on CRAN. Below a figure about their monthly download stats as provided from the package dlstats.


Since beginning of the month I am tenured!

At that occassion I would also like to point out that many new papers are out. See my publication list for details. To give an impression of my research I also added below a word cloud of the abstracts of my published articles.

Invited speaker at ICORS 2019

I’m heading to ICORS as an invited speaker and will give a talk about robust approaches for blind source separation. This will be the first time I get to visit Ecuador!

400 000€ Grant!

Great news! The Austrian Science Fund (FWF) will fund my
project “Blind Source Separation in Time and Space” with almost 400000 Euros.

Several new papers out

It has been a while since my last post – several papers have appeared since then, like

  1. “Supervised Dimension Reduction for Multivariate Time Series” appeared in  Econometrics and Statistics.
  2. “Independent Component Analysis for Tensor-valued Data” appeared in the Journal in the Multivariate Analysis. For a short time it can be downloaded at here.
  3. I presented our paper “Blind Source Separation For Nonstationary Tensor-Valued Time Series” at the IEEE International Workshop on Machine Learning for Signal Processing. It should appear soon IEEE Xplore.

More details are also on my list of publications.