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Current PhD students:

  1.  Christoph Mühlmann: Blind source separation for spatial data. (TU Wien)

Previous PhD students:

  1.  Jari Miettinen (2014): On statistical properties of blind source separation methods based on joint diagonalization. (University of Jyväskylä, jointly with Sara Taskinen)
  2. Aurore Archimbaud (2018): Statistical methods for outlier detection for high-dimensional data. (Toulouse School of Economics, jointly with Anne Ruiz-Gazen)
  3. Markus Matilainen (2018): On independent component analysis and supervised dimension reduction for multivariate time series. (University of Turku, jointly with Hannu Oja)
  4. Joni Virta (2018): Independent component analysis for non-standard data structures. (University of Turku, jointly with Hannu Oja and Bing Li)

Currently supervised Master theses:

  1.  Gregor Fischer: Blind source separation for compositional time series. (TU Wien, jointly with P. Filzmoser)
  2.  Christoph Kösner: On estimating the signal dimension in tensorial PCA. (TU Wien, jointly with J. Virta)
  3. Lea Flumian: On stationary subspace analysis. (TU Wien)

Previously supervised Master’s theses:

  1. Juho Pelto (2016): Estimation of signal space in principal components analysis . (University of Turku, jointly with H. Oja)
  2. Matti Rytkönen (2014): On multivariate regression using spatial signs and ranks. (University of Tampere)
  3. Simo Korpela (2013): Comparing the performance of multivariate location tests for Lp-norm distributed data. (University of Tampere)
  4. Päivi Julin (2013): Palvelu- ja toimitilarakentamisen ennakoivat indikaattorit ja ennustamisen mallintaminen. (University of Tampere, jointly with A. Luoma)
  5. Eero Liski  (2009): On sliced inverse regression. (University of Tampere, jointly with H. Oja)

Currently supervised Bachelor theses:

  1.  Thomas Janka: A Shiny app for exploratory projection pursuit. (TU Wien)
  2.  Josip Grgic: On robust BSS. (TU Wien)

Previously supervised Bachelor’s theses:

  1. Max Griesmayer (2019): Automatic outlier detection for haemodynamic tilt-table data. (TU Wien)
  2. Christoph Kösner (2019): Computational aspects of kernel ICA. (TU Wien)
  3. Matthäus Kerres (2018): “Prophet” – time series predition using generalized additive models. (TU Wien)