Automatic Control

Faculty of Engineering, LTH

Automatic Control  

LTH best Master's thesis

Johanna Wilroth has been awarded the prize "LTHs Jubileumsstipendium 2020" for the best master thesis at LTH. In her thesis "Domain Adaptation for Attention Steering," Wilroth studied novel algorithms for improving the performance of hearing aids using EEG signals in combination with auditory input. The master thesis was done at the Department of Automatic Control, with Carolina Bergeling as main supervisor, in collaboration with the research center Eriksholm/Oticon in Denmark. The collaboration also involved the departments of Psychology and Mathematical Statistics at Lund University.

Paper Award

We congratulate Marcus Greiff (to the right in the photo) and co-authors Anders Robertsson (left) and Karl Berntorp (middle) who was awarded the 2020 IEEE CCTA Best Student Paper Award for the paper "MSE-Optimal Measurement Dimension Reduction in Gaussian Filtering”.


Seminar by S. Wengel Mogensen: Causal inference in dynamical systems


From: 2021-03-02 13:15 to 14:00
Place: Zoom:
Contact: bo [dot] bernhardsson [at] control [dot] lth [dot] se
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Title: Causal inference in dynamical systems

Speaker: Søren Wengel Mogensen, Dept. of Automatic Control, LTH


Many questions in science are causal in the sense that they aim to describe the mechanisms that govern observed data and not just the observed correlations. Sometimes we can use prior knowledge of the data generation to reason about cause and effect, and through experiments we can learn about an unknown or partially unknown system. In this talk, we discuss how one can formalize 'cause' and 'effect' and describe ideas behind some of the methods that one can use to learn about the causal structure in systems where we can only do a limited set of experiments, if any at all.


Zoom link:

Recent Publications

Welcome to KC4!

In May, we moved to temporary offices at KC4 in Kemicentrum. Here we will stay for two years while the M-building is being renovated. See "contact" (in About) for the new visiting adress.

Formula Student

The department has a collaboration with the Lund Formula Student team, who are developing a fully autonomous race car to compete in Formula Student events all across Europe. They are always looking for interested and talented team members. If you are interested in a wide variety of technologies such as neural networks, control theory, ROS, etc, please visit their website or contact them at: