Currently, I am leading a Reinforcement Learning Team at PLUS University in Salzburg. Applications range from theoretical aspects - basic research - to real-world applications in local industry. If you have interest to collaborate please reach out to me.
In general, I am interested in the development and application of robust, modern AI systems that make good decisions under uncertainty.
I believe that human and artificial intelligence are complementary and that the combination of the two is of great benefit in finding solutions to our current global problems.
My team focuses besides of different flavours of reinforcement learning on multivariate time series and analytics, Bayesian methods, control theory and physics.
The study of artificial intelligence is currently one of the most interesting topics in the world...
Recent activities:
- I co-organised the RL4 Autonomoous Accelerators workshop in Hamburg 2025, 02 - 04 February 2024
- I co-organised a RL Bootcamp: 25-27.September.
- I had the opportunity to give a TEDx talk: AI is what we make it.
- I organised the RL4 Autonomoous Accelerators workshop in Salzburg 2024, 05 - 07 February 2024
- I am and have been involved in multiple contract research projects with local industry partners such as Palfinger, Copa Data, and W&H, both in the past and ongoing.
- In the realm of fundamental research focusing on control systems and reinforcement learning, I am engaged in collaborative efforts with several esteemed institutions, including CERN, DESY, KIT, SLAC, and GSI, among others.
Teachings at the University of Salzburg (PLUS):
- Special topics in Data Science.
- Introduction into Deep Reinforcement Learning.
- Introduction to Reinforcement Learning.
- Advanced topics in Reinforcement Learning.
- Mathematical foundations in Precision Medicine.
Current students:
- Sabrina Pochaba - Data Science PhD: Multi-agent reinforcement learning in D2D communication
- Sahan Warnakulasooriya Dabarera Data Science Master: - Adaptive Navigation for UGVs and USVs: Enhancing Nav2 for Wind-Disturbed Environments
- Olga Mironova - Data Science Master: Do you really think about consequences? Bridging Classical Control and Reinforcement Learning for Delayed Outcome Optimisation
- Benjamin Halilovic - Data Science Master: Robust Multi-Turn Injection at SIS18 via Gaussian Process Model Predictive Control
- Maximilian Tengler - Artificial Intelligence Bachelor: Reinforcement Learning benchmarking on AWAKE
- Reuf Kozlica - Data Science PhD: Hierarchical reinforcement learning in assembly line optimization
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Secondary supervision:
- Raoul Kutil - Data Science PhD: Knowledge Graphs in medicine
- Juan Manuel Montoya Bayardo - Data Science PhD: Reinforcement learning in nautical robotics
- Georg Schaefer- Reinforcement learning in cyber-physical systems
- Olivia Zechner: Towards AI-Driven Adaptive Virtual Environments, based on Biosignals: XR training to improve decision-making and acting in stressful situations
- Jakob Uhl: Tangible XR for Training of Challenging Occupations: Increasing Presence and Sensory
Former students:
- Lukas Lamminger (finished May 2023) - Data Science Master: Model based and Meta reinforcement learning in accelerator physics
- Sascha Schuster (finished March 2023) - Data Science Master: Reinforcement learning in medicine (DTR of insulin dosing)