Ph.D. Students (main supervisor)

  • Måns Magnusson (Statistics) – Topic: Large Scale Topic Modeling of Text.
  • Josef Wilzén (Statistics) – Topic: Bayesian Analysis of Neuroimaging Data.
  • Per Sidén (Statistics) – Topic: Spatial Models in Neuroimaging.
  • Hector Rodriguez-Deniz (Statistics) – Topic: Bayesian Learning for Spatio-Temporal Models in Transportation.

Ph.D. Students (co-supervisor)

  • Olov Andersson (Machine Learning/CS) – Topic: Machine Learning for Robotics.
  • Johan Falkenjack – (Machine Learning/CS)- Topic: Natural Language Processing. Readability of texts.
  • Sarah Alsaadi (Statistics) – Topic: Psychometrics. Multi-level models.
  • Munezero Parfait (Statistics, SU) – Topic: Bayesian survival analysis.
  • Caroline Svahn (Statistics) – Topic: Machine Learning for 5G System – Control and Automation.

Ph.D. Graduates (main supervisor)

Ph.D. Graduates (co-supervisor)

  • Roy Chandran (Machine Learning/CS) – Topic: Neural Networks for Hurricane Prediction.
  • Christian Tallberg – Thesis: Bayesian and Other Approaches for Analyzing Network Block-Structures (joint with Ove Frank). Ph.D. in Statistics, Stockholm University, 2003.