My main research interest is nonlinear inference, especially within the context of dynamical systems, solved using probabilistic models and algorithms. In terms of scientific fields, my research is situated somewhere on the intersection between the fields of machine learning, signal processing and automatic control. My aim is to pursue both basic and applied research, where the latter is typically carried out in close collaboration with industry. A brief overview of my research is available here and my publications are available here.
The group is expanding! We are looking for a new colleague (Associate Professor or Professor) in Signal Processing. The formal advertisment is available here. Feel free to send me an e-mail if you have any questions.
Recent research results/news
January 29, 2015: The details concerning the one-day tutorial that I will give on nonlinear system identification using sequential Monte Carlo (SMC) methods are now available. The tutorial is given as a part of the Summer School on Foundations and advances in stochastic filtering, which will be held in Barcelona, June 22-26, 2015.
January 26, 2015: The sequential Monte Carlo (SMC) workshop will be held in Paris in August. More information is available from here, where you can also register.
January 23, 2015: The website for the Uppsala CARS (Camera-based Autonomous Racing System) project is now available here! If you are student here in Uppsala interested in working on this project, let us know since we are currently in the process of assembling a new team. Some ideas for future projects are available here, but own ideas are of course also welcome.
December 29, 2014: Over the last 5 years we have been working on the problem of combining information (sensor fusion) from inertial sensors (accelerometers and gyroscopes) and ultra-wideband (some early results are available here and here). Our new work provides a general solution based on a formulation of the problem as an optimization problem. The present application is indoor positioning. This work has now been accepted for publication in the IEEE Transactions on Vehicular technology (special section on Indoor localization, tracking, and mapping with heterogeneous technologies)
Manon Kok, Jeroen D. Hol and Thomas B. Schön. Indoor positioning using ultra-wideband and inertial measurements. IEEE Transactions on Vehicular Technology (special section on Indoor localization, tracking, and mapping with heterogeneous technologies), 2015. (accepted for publication) [pdf]
December 27, 2014: Kaczmarz's algorithm is an iterative method for solving linear systems of equations published by the Polish mathematician Stefan Kaczmarz back in 1937, here is an English translation of the original paper (Angenäherte Auflösung von Systemen linearer Gleichungen). We have studied the exponentional convergence of Kaczmarz's algorithm and we provide upper bounds of its convergence rate. The analysis is inspired by proofs of stability for linear time-varying dynamical systems from the control community. The work has been provisionally accepted for publication in the IEEE Signal Processing Letters. There is still room to find tighter upper bounds.
Liang Dai and Thomas B. Schön. On the exponential convergence of the Kaczmarz algorithm. IEEE Signal Processing Letters, 2015.
December 17, 2014: We have been invited to present our optimization-based solution to the human body motion capture problem at the conference on Technically Assisted Rehabilitation (TAR 2015) held in Berlin, Germany in March 2015.
Manon Kok, Jeroen Hol and Thomas B. Schön. An optimization-based approach to human body motion capture using inertial sensors. Conference on Technically Assisted Rehabilitation (TAR), Berlin, Germany, March, 2015. (invited paper). A more complete description of this work is available here.
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