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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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). -
Non-parametric time-domain tremor quantification with smart phone for therapy individualization. In IEEE Transactions on Control Systems Technology, volume 28, 2020. (DOI). Publication status: Epub ahead of print
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TWIST tenecteplase in wake-up ischaemic stroke trial. In European Journal of Neurology, volume 26, number 1, SI, WILEY, 2019.
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Consensus statements and recommendations from the ESO-Karolinska Stroke Update Conference, Stockholm 11-13 November 2018.. In European Stroke Journal, volume 4, number 4, pp 307-317, 2019. (DOI).
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Fluoxetine for stroke recovery: Meta-analysis of randomized controlled trials.. In International Journal of Stroke, 2019. (DOI). Publication status: Epub ahead of print
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Trends in stroke reperfusion treatment and outcomes in New Zealand.. In Internal medicine journal (Print), 2019. (DOI). Publication status: Epub ahead of print
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Selective serotonin reuptake inhibitors (SSRIs) for stroke recovery.. In Cochrane Database of Systematic Reviews, volume 2019, number 11, 2019. (DOI).
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Joint Axis Estimation for Fast and Slow Movements Using Weighted Gyroscope and Acceleration Constraints. In , 2019. (fulltext:postprint
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Visualization of convolutional neural network class activations in automated oral cancer detection for interpretation of malignancy associated changes. In 3rd NEUBIAS Conference, Luxembourg, 2-8 February 2019, 2019.
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Control-Engineering Perspective on Deep Brain Stimulation: Revisited. In , 2019. (DOI).