Research Team

Our team at the Smart Analytics & Reinforcement Learning (SARL) group, part of the IDA Lab at Paris Lodron University Salzburg (PLUS), is dedicated to advancing AI through research spanning from theoretical foundations to real-world applications.

Research Staff

OM
Olga Mironova
Research Assistant
Contributing to the INSPIRE project (AI-driven personalized instruction in STEM education). MSc thesis Bridging Classical Control and RL via Structured Priors — 100/100.
SG
Sina Garazhian
Research Assistant
Reinforcement Learning & Robot Learning

PhD Students

Primary supervision of doctoral candidates working on cutting-edge RL and AI research.

SP
Sabrina Pochaba
PhD Student
Multi-Agent Reinforcement Learning for Resource Allocation in Wireless Network Communication (D2D)
ST
Sarah Trausner
PhD Student
FOCUS: Forecasting and Optimization under Constraints and Uncertainty for Sustainable Industrial Energy Systems
CS
Christoph Schranz
PhD Student
Contactless Monitoring Beyond Ballistocardiography
RK
Reuf Kozlica
PhD Student
Hierarchical Reinforcement Learning in Assembly Line Optimization
GS
Georg Schaefer
PhD Student
Reinforcement Learning in Cyber-Physical Systems
MD
Markus Dygruber
PhD Student
INSPIRE: Intelligent Novel Support for Personalized Instruction and Robust Evaluation in STEM

Master Students

LX
Laya Shibu Xavior
MSc Student
Regelungsoptimierung von Piezoantrieben (RL-PD)
SD
Sahan Warnakulasooriya Dabarera
MSc Student
Adaptive PID Tuning via Meta-Reinforcement Learning
BH
Benjamin Halilovic
MSc Student
Robust Multi-Turn Injection at SIS18 via Gaussian Process Model Predictive Control
JL
Julian Langschwert
MSc Student
Online Parameter Identification via Reinforcement Learning Integrated with Model Predictive Control

Bachelor Students

MT
Maximilian Tengler
BSc Student
Reinforcement Learning Benchmarking on AWAKE
KG
Kevin Gajic
BSc Student
Agentic AI
SR
Stefan Reiter
BSc Student
Contracts and AI – Risk, Regulation, and Strategic Impact
FM
Fabio Matanza
BSc Student
Control of a Liquid-Propellant Rocket Engine using Reinforcement Learning
AB
Armin Brückl
BSc Student
Reinforcement Learning
MP
Maria Pape
BSc Student
Welche Methoden ermöglichen die Einbettung domänenspezifischen Unternehmenswissens in KI-Systeme?
KB
Kajsa Björkbom
BSc Student
Reinforcement Learning Beyond Greedy Optimisation for Delayed-Consequence Accelerator Control

Secondary Supervision

Co-supervision and advisory roles for doctoral students.

  • Raoul Kutil — Data Science PhD: Knowledge Graphs in medicine
  • Juan Manuel Montoya Bayardo — Data Science PhD: Reinforcement Learning in Nautical Robotics
  • 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

Alumni

Former students who have successfully completed their theses.

  • Olga Mironova (finished 2026) — MSc: Do you really think about consequences? Bridging Classical Control and Reinforcement Learning for Delayed Outcome Optimisation — 100/100
  • David Graf (finished 2025) — Now PhD at Geomar/MarData Kiel: Inverse Reinforcement Learning
  • Lukas Lamminger (finished May 2023) — MSc: Model-Based and Meta Reinforcement Learning in Accelerator Physics
  • Sascha Schuster (finished March 2023) — MSc: Reinforcement Learning in Medicine (DTR of Insulin Dosing)

Interested in joining our team?
We welcome motivated students interested in Reinforcement Learning, AI safety, and applications in healthcare, robotics, and industrial systems. Feel free to reach out at simon.hirlaender@plus.ac.at.