David Ohlin
About me
PhD student in automatic control since 2021. Part of WASP (Wallenberg AI, Autonomous Systems and Software Program). MSc in Engineering Physics, graduated in 2021 with master's thesis on machine learning methods for interpreting EEG signals.
Research and Publications
Research interests include data-driven control, control of large-scale networks and its application to social networks, opinion modeling and EEG signal processing.
Publications
"Achieving consensus in networks of increasingly stubborn voters" to be published at the 61st IEEE Conference on Decision and Control (CDC 2022).
Teaching
Fall 2021
- FRTN05 - Non-linear control and servo systems
Spring 2022
- FRTN75 - Learning-based control
- FRTN30 - Network dynamics