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.
Recent research results/news
August 21, 2015: During this week a team consisting of Johan Wågberg, Kjerstin Johansson, Johan Karlsson, Mohammed Al Abassi and myself participated in the Swedish study group Mathematics in Industry at Institute Mittag-Leffler. We worked on solving the problem of energy disaggregation that Greenely is facing, see also this blog post.
July 28, 2015: In 2005 we published a paper on Rao-Blackwellized particle filters (available here). Ten years later our paper sorting out the details concerning Rao-Blackwellized particle smoothing is now accepted for publication. This opens up also for offline inference in conditionally linear Gaussian models. Our construction is such that we marginalize out a conditionally tractable subset of state variables, effectively making use of sequential Monte Carlo only for the intractable (i.e. the nonlinear/non-Gaussian) part of the model.
Fredrik Lindsten, Pete Bunch, Simo Särkkä, Thomas B. Schön and Simon J. Godsill. Rao-Blackwellized particle smoothers for conditionally linear
Gaussian models. IEEE Journal of Selected Topics in Signal Processing, 2015. (Accepted for publication) [arXiv]
June 21, 2015: The slides for tomorrow’s lectures on Nonlinear system identification using sequential Monte Carlo methods are now finished [Lecture 1], [Lecture 2], [Lecture 3], [Lecture 4]. These lectures form a course within the Summer school on foundations and advances in stochastic filtering (FASF 2015) held here in Barcelona, Spain during June 22-25, 2015. It is an updated version of the guest lectures given in Brussels a few weeks back and it is based on this paper.
June 7, 2015: The slides for tomorrow’s lectures on Nonlinear system identification using sequential Monte Carlo methods are now finished [Lecture 1], [Lecture 2], [Lecture 3], [Lecture 4]. These lectures are given in connection with the the Doctoral school on nonlinear system identification held in Brussels, Belgium. They are based on our recent tutorial paper on the topic, available here. In case you find this interesting I will give another edition in Barcelona, Spain on June 22, more information about how to register can be found here.
May 31, 2015: Together with Fredrik Lindsten and Bhushan Gopaluni I am organizing an invited session on the use of Sequential Monte Carlo methods for inference in nonlinear dynamical systems. It was just accepted for the 17th IFAC Symposium on System Identification (SYSID) to be held in Beijing in China, October 2015.
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