Research at Systems and Control
Modeling, inference and control in complex dynamical systems
Current projects
Dynamical systems, physical and others, can be described by a variety of mathematical models. We develop methods for modeling and estimation of dynamical systems based on measurements of input/output data. The models can be used for analysis, in order to better understand the properties of the system, or for control, to automatically regulate a process without human interaction. Contact person: Alexander MedvedevAutomatic control and System identification
Many interesting phenomena around us are complex, dynamical and stochastic in nature, and the available data are inherently uncertain. We develop theory and tools for learning, reasoning and acting based on probabilistic models and measured data, methods that allow humans and machines to better understand the surrounding world. Contact person: Thomas SchönStatistical Machine Learning
The goal of signal processing is to extract information from measured quantities, or signals. This broad concept ranges from simple linear filtering of time series to reduce noise, to nonlinear parameter estimation based on high-dimensional data using statistical models. Estimation theory, optimization, and statistics, play central roles. Contact person: Thomas SchönSignal Processing
Important application areas
The theory and methods of dynamical systems, control, identification and signal processing have much to offer research and clinical practice in modern medicine. We develop methods used in the diagnosis, assessment, and treatment of medical conditions, based on dynamical models of physiological and biological systems. Currently we have projects on Parkinson's disease, breast cancer, diabetes and balance impairment. Contact person: Alexander MedvedevBiomedical systems
Water quality and treatment of water is a growing concern around the world. Demands on quality and increasing loads call for optimized operation of wastewater treatment plants. Applied research in automatic control is an important tool in improving the performance of treatment plants. We are developing control and estimation strategies for wastewater treatment plants that improve pollutant removal, reduce the need for chemicals and yield energy savings. Contact person: Bengt CarlssonWastewater engineering
Recent publications
More comprehensive list of publications
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Automatic diagnosis of the 12-lead ECG using a deep neural network
. In Nature Communications, volume 11, number 1, NATURE PUBLISHING GROUP, 2020. (DOI, Fulltext, fulltext:print
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Timed Up-and-Go Dual-Task Testing in the Assessment of Cognitive Function: A Mixed Methods Observational Study for Development of the UDDGait Protocol. In International Journal of Environmental Research and Public Health, volume 17, number 5, MDPI, 2020. (DOI, Fulltext, fulltext:print).
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Frequency domain identification of FIR models in the presence of additive input-output noise. In Automatica, volume 115, PERGAMON-ELSEVIER SCIENCE LTD, 2020. (DOI).
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Identifying reionization-epoch galaxies with extreme levels of Lyman continuum leakage in James Webb Space Telescope surveys. In Monthly notices of the Royal Astronomical Society, volume 491, number 4, pp 5277-5286, OXFORD UNIV PRESS, 2020. (DOI).
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Microstructures and mechanical properties of Al2O3/YAG:Ce3+ eutectics with different Ce3+ concentrations grown by HDS method. In Journal of Alloys and Compounds, volume 816, 2020. (DOI).
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Nonparametric time-domain tremor quantification with smart phone for therapy individualization. In IEEE Transactions on Control Systems Technology, volume 28, number 1, pp 118-129, 2020. (DOI).
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Online tissue conductivity estimation in Deep Brain Stimulation. In IEEE Transactions on Control Systems Technology, volume 28, number 1, pp 149-162, 2020. (DOI).
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Conditionally Independent Multiresolution Gaussian Processes. In 22nd International Conference On Artificial Intelligence And Statistics, Vol 89, volume 89 of Proceedings of Machine Learning Research, 2019.
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Deep convolutional networks in system identification. In Proc. 58th Conference on Decision and Control, pp 3670-3676, IEEE, 2019. (DOI).
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Identification of continuous Volterra models with explicit time delay through series of Laguerre functions. In Proc. 58th Conference on Decision and Control, pp 5641-5646, IEEE, 2019. (DOI).