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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)
- Matias Quiroz – Thesis: Bayesian Inference for Large Data Problems. Ph.D. in Statistics, Stockholm University, 2015.
Currently post doc in Statistics at UNSW, Sydney.
- Feng Li – Thesis: Bayesian Modeling of Conditional Densities. Ph.D. in Statistics, Stockholm University, 2013.
Awarded the 2014 Cramér prize for best PhD thesis in Statistics and Mathematical Statistics.
Currently Assistant Professor, Central University of Finance and Economics, Beijing, China.
- Bertil Wegmann – Thesis: Bayesian Inference in Structural Second-Price Auctions. Ph.D. in Statistics, Stockholm University, 2011.
Currently Assistant Professor at Division of Statistics and Machine Learning, Linköping University.
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.