Present team

A list of my co-authors is available here and previous members of the team are listed here


Niklas Wahlström (previously at Linköping University), deep learning and Gaussian processes.
Jalil Taghia (previously at Stanford University), variational inference, sampling based methods and deep learning.
Juozas Vaicenavi
čius (previously at UU, mathematics), deep learning for autonomous driving jointly with Veoneer.
Jack Umenberger (previously at University of Sydney), nonlinear system identification and optimization.
Koen Tiels (previously at 
Vrije Universiteit Brussel, Belgium), nonlinear systemidentification and optimization.
Andreas Lindholm (previously at UU, Machine Learning), Machine Learning applications and nonlinear inference. 

PhD students

Thomas Schön is currently supervising the following PhD students:

Christian Andersson Naesseth Defending on December 14, 2018. Thesis title: Machine learning using approximate inference - Variational and sequential Monte Carlo methods.
Johan Wågberg Thesis topic: 
Bayesian nonparametric models for system identification.
Carl Andersson Thesis topic: Data-driven system identification using deep learning.
Carl Jidling Thesis topic: Gaussian processes and the automation of probabilistic modeling.
Maria Bånkestad Thesis topic: Deep non-parametric models. Industrial PhD student with RISE SICS.
Fredrik Gustafsson Thesis topic: Uncertainty-aware deep learning for autonomous driving and medical imaging. 
Niklas Gunnarsson (Starting in November 2019, industrial PhD student with Elekta)

Thomas Schön is actively co-supervising the following PhD students:

Jan Kudlicka Thesis topic: Sequential Monte Carlo and probabilistic programming.
Muhammad Osama Thesis topic: Data-driven Spatio-temporal modelling.


Johannes HendriksThe University of Newcastle, Australia, November 2018 - February 2019. Working on tomographic reconstruction and Gaussian processes.
Antônio Ribeiro
Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil. September 2018 - September 2019. Working on the intersection of Machine Learning and Control.

 © Thomas Schön 2018