Department of Computer Science

PhD Students

  • Robert Deibel (2023): Development of RL training pipeline, Research towards use of sequence modells in RL agents and utilization of first- and second-order metrics for debugging and interpretation of RL training.

Masters Students

  • Abay A. (2024) Neural image compression methods for training reinforcement learning agents.
  • Felix P. (2024) Investigating the integration of second-order optimiyation strategies in reinforcement learning.
  • Jasha p. (2023) Data augmentation for real world reinforcement learning robotic applications.
  • Virmarie M. (2023) Exploring the effects of scanpath feature engineering for supervised image classification models.
  • Michael H. (2022) Efficient Training of LSTMs for Supervised and Reinforcement Learning Tasks.
  • Shudao W. (2022) Practical Improvement in Robotic Reinforcement Learning.

Bachelors Students

  • Sebastian B. (2024) Analysing deep reinforcement learning training with first and second-order gradient statistics
  • Julia L. (2023) Mind wandering detection with eye tracking and machine learning.
  • Maximilian H. (2022) Creating and controlling a digital twin for a bioreactor.
  • Valentina D. (2021) Enhancing reproducibility of deep learning research using ML Ops tools.

Working Students

  • Philipp T.; Benchmarking Reinforcement Learning algorithms
  • Maximilian H.; Develop derivative-free optimization techniques