Stefan Stojanovic

I am a 2nd year PhD student at the Division of Decision and Control Systems (DCS) of the School of Electrical Engineering and Computer Science. I carry my research under the supervision of Prof. Alexandre Proutiere and Prof. Mikael Johansson. Prior to that, I completed a MSc degree in Electrical Engineering and Information Technology from ETH Zurich with distinction.

Research

My primary research area is Reinforcement Learning. So far, my focus has been on establishing theoretical guarantees for problems with a specific low-dimensional structure in settings such as model-based RL, contextual bandits, and model-free RL. Currently, I am interested in offline reinforcement learning, which involves leveraging already collected data to learn a task at hand.

If you are interested in my publications (Neurips, ICML, ALT...) please check my Google Scholar page. My research is supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP-AI), funded by the Knut and Alice Wallenberg Foundation.

Supervision

I supervise bachelor's and master's theses related to my research area. Here are some examples of the work I've supervised:

• “Adaptive Reinforcement Learning for Real-World Systems with Delays” by Iga Pawlak (co-supervised with ABB)

• “Frameskipping and Exploration Strategies for Deep Q-Networks” by Niklas Rolin and Vaka Soleyjardottir

• “Multi-Agent Control in Warehousing: A Deep Q-Network Approach” by Adam Fischer and Martin Wilen

If you are a bachelor's or master's student at KTH interested in working on Reinforcement Learning, please contact me via email.