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, Fethi Bencherki and Emma Tegling: "Achieving consensus in networks of increasingly stubborn voters", 61st IEEE Conference on Decision and Control. December 2022.
David Ohlin, Emma Tegling and Anders Rantzer. "Optimal Control of Linear Cost Networks", 22nd European Control Conference. November 2023. (accepted)
Luka Baković, David Ohlin, Giacomo Como and Emma Tegling: "Multipolar opinion evolution in biased networks". IEEE Control Systems Letters. June 2024. (accepted)
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. (accepted)
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
