Signals and Systems
We study many different problems in signal processing, automatic control, machine learning and wireless communications.
The Division of Signals and Systems (SOS) conducts research and teaching in signal processing, automatic control, machine learning and wireless communications. We research on security for control systems, detection, harvesting based wireless sensor networks, vehicle platoons, audio signal processing and 5G/6G.
We have two PhD programs: Electrical Engineering with Specialisation in Signal Processing and Electrical Engineering with Specialization in Automatic Control.
Our research is primarily financed by the Swedish Research Council (VR), The Foundation for Strategic Research (SSF), Sweden's Innovation Agency (VINNOVA), The Swedish Research Council for Sustainable Development (FORMAS) and The Knut and Alice Wallenberg Foundation KAW.
Research areas
Signal Processing and Wireless Communications
We study everything from energy efficiency in wireless sensor networks, energy harvesting and wireless power transfer, to 5G/6G communication and distributed machine learning.

Automatic Control, Robotics, Security and Privacy
Our research includes everything from intelligent systems, multiagent control and networked control systems, to cybersecure machine learning.

Audio and Acoustic Signal Processing
We research on improving the sound quality of audio systems, digital correction of the room and loudspeaker acoustics, Active Noise Control (ANC), and Acoustic Zones.

Our latest publications at the Division of Signals and Systems
- Kullback-Leibler Divergence-Based Filter Design Against Bias Injection AttacksTosun, Fatih Emre; Teixeira, André; Dong, Jingwei et al., 2026
- A linearly convergent distributed heavy-ball GNE seeking algorithm for aggregative games over weight-unbalanced digraphs via finite-time consensusChen, Xiaomeng; Ding, Kemi; Dey, Subhrakanti et al., 2026
- Efficiently computing the cyclic output-to-output gainArnström, Daniel; Teixeira, André, 2026
- Prescribed-Time Observer Is Naturally Robust Against Disturbances and Unmodeled DynamicsAbedou, Abdelhadi; Mameche, Omar, 2026
- UAV-Assisted Sensing Intelligence for Remote State Estimation: A Joint Scheduling and Matching ApproachCai, Zai; Qin, Jieyuan; Quevedo, Daniel E. et al., 2026