Smart Analytics & Reinforcement Learning (SARL)

Research Team & Supervision

Our research group at the IDA Lab focuses on the mathematical foundations of Reinforcement Learning, symplectic world models, and data-driven autonomous control for critical physical and industrial systems.

Doctoral Candidates (PhD)

Primary supervision of doctoral researchers advancing theoretical RL and mission-critical applications.

SP
Sabrina Pochaba
Data Science PhD
Multi-Agent Reinforcement Learning for Resource Allocation in Wireless Network Communication
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
Data Science PhD
Hierarchical reinforcement learning in assembly line optimization
GS
Georg Schaefer
PhD Student
Improving Trajectory Tracking by Augmenting States with Future Targets
MD
Markus Dygruber
PhD Student
INSPIRE: Intelligent Novel Support for Personalized Instruction and Robust Evaluation in STEM

Master Students (MSc)

Supervised master theses in Data Science, Artificial Intelligence, and Computer Science.

OM
Olga Mironova
Data Science Master
Causal GP-MPC: Where Structure, Safety, and Online Learning Meet
BH
Benjamin Halilovic
Data Science Master
Robust Real-Time Optimization of SIS18 Injection using Gaussian Process MPC
JL
Julian Langschwert
Master Student
Online Parameter Identification via Reinforcement Learning Integrated with Model Predictive Control
SD
Sahan Warnakulasooriya Dabarera
Data Science Master
Adaptive PID Tuning via Meta-Reinforcement Learning
LX
Laya Shibu Xavior
Master Student
Regelungsoptimierung von Piezoantrieben

Bachelor Students (BSc)

Undergraduate research projects and theses in AI and Computer Science.

SR
Stefan Reiter
AI Bachelor
Contracts and AI: Risk, Regulation, and Strategic Impact
FM
Fabio Matanza
AI Bachelor
Curriculum-Guided PPO for LUMEN Engine
AB
Armin Brückl
CS Bachelor
TBD topic in Reinforcement Learning

Secondary Supervision & Advisory Roles

  • Graduiert Juni 2026 Kevin Gajic: AI Bachelor, Agentic AI Systems and Autonomous Multi-Step Tool Execution
  • Raoul Kutil: Data Science PhD, Knowledge Graphs in medicine
  • Juan Manuel Montoya Bayardo: Data Science PhD, Binary Trigger Signals for Deep RL in Equity Trading / Nautical Robotics
  • Olivia Zechner: Towards AI-Driven Adaptive Virtual Environments, based on Biosignals (XR stress decision-making)
  • Jakob Uhl: Tangible XR for Training of Challenging Occupations: Increasing Presence and Sensory Feedback

Alumni

Former students who have successfully completed their degree theses under our supervision.

  • Finished 2026 Kajsa Bjoerkbom: Bachelor, Reinforcement Learning Beyond Greedy Optimisation for Delayed-Consequence Accelerator Control
  • Finished 2026 Maximilian Tengler: AI Bachelor, Reinforcement Learning Beyond Greedy Optimisation
  • Finished 2026 Maria Pape: Bachelor, Welche Methoden ermöglichen die Einbettung domänenspezifischen Unternehmenswissens in KI-Systeme?
  • Finished 2023 Lukas Lamminger: Data Science Master, Model based and Meta reinforcement learning in accelerator physics
  • Finished 2023 Sascha Schuster: Data Science Master, Reinforcement learning in medicine (DTR of insulin dosing)

Join the SARL Team

We welcome motivated students with a strong mathematical or computational background interested in Reinforcement Learning, AI safety, physics-informed models, and high-precision control.

Propose a Topic or Inquire