Present team

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


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.
Riccardo Sven Risuleo (perviously at KTH), Gaussian processes, dynamical systems.

PhD students

Thomas Schön is currently supervising the following PhD students:

Johan Wågberg Thesis topic: Bayesian nonparametric models for system identification.
Carl Andersson Thesis topic: Data-driven sequence learning using deep architectures.
Carl Jidling Thesis topic: Gaussian processes and the optimization problems 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 Thesis topic: Learning to control in uncertain environments, magnetic resonace radiation therapy. WASP Industrial PhD student with Elekta.
Daniel Gedon (starting in mid-August)

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 and causal inference.


Antônio RibeiroUniversidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil. September 2018 - December 2019. Working on the intersection of Machine Learning and Control.

 © Thomas Schön 2019