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. Currently, I work with the application of graph search methods to optimal control of positive systems. My research also includes nonlinear dynamical models of network synchronization, with applications to opinion dynamics.
Research and Publications
ORCID: https://orcid.org/0000-0003-2838-6753
Research interests include optimal control, control of large-scale networks and its application to social networks, opinion modeling and EEG signal processing.
Publications
David Ohlin, Richard Pates and Murat Arcak: "On Exact Solutions to the Linear Bellman Equation". IEEE Control Systems Letters. 2025.
Luka Baković, David Ohlin, Giacomo Como and Emma Tegling: "Multipolar opinion evolution in biased networks". IEEE Control Systems Letters. 2024.
David Ohlin, Anders Rantzer and Emma Tegling: "Heuristic Search for Linear Optimal Control". 26th International Symposium on Mathematical Theory of Networks and Systems. Extended
abstract. June 2024.
David Ohlin, Emma Tegling and Anders Rantzer. "Optimal Control of Linear Cost Networks", European Journal of Control, Vol. 80. November 2024.
David Ohlin, Fethi Bencherki and Emma Tegling: "Achieving consensus in networks of increasingly stubborn voters", 61st IEEE Conference on Decision and Control. December 2022.
Supervised Thesis Projects
Swartling Sennhed, Johan: "On Dynamic Stubbornness in the Concatenated Friedkin-Johnsen Model". Bachelor thesis. 2024.
Teaching
Fall 2021
- FRTN05 - Non-linear control and servo systems
Spring 2022
- FRTN75 - Learning-based control
- FRTN30 - Network dynamics
Spring 2023
- FRTN75 - Learning-based control
- FRTN30 - Network dynamics
Spring 2024
- FRTN75 - Learning-based control
- FRTN30 - Network dynamics
Spring 2025
- FRTN75 - Learning-based control
- FRTN30 - Network dynamics
Fall 2025
- FRTF05 - Automatic Control, Basic Course
Spring 2026
- FRTN75 - Learning-based control
