Maximilian Schier, M. Sc.
Leibniz Universität Hannover
Schneiderberg 32
30167 Hannover
phone: +49 511 762-5038
fax: +49 511 762-5333
office location: room 232


Maximilian Schier studied Computer Science at Leibniz University Hannover. He completed his master thesis on the topic of Deep Image Clustering in July 2021. His current research focuses on Reinforcement Learning and dynamic representations, e.g. graphs, but he is also involved with projects on panoptic segmentation of bio-medical images.

Research Topics

  • Graph Neural Networks for scene representations
  • Dynamic scene representations in general
  • Reinforcement Learning in an automotive/traffic context
  • Deep & Reinforcement Learning for autonomous racing
  • Panoptic Segmentation for Biology/Medicine.

If you are interested in a thesis regarding above topics, do not hesitate to contact me. As inspiration for for example a bachelor thesis, here is a toy problem of a Soft Actor-Critic Reinforcement Learning agent controlling a vehicle End-to-End (sensors to actuators):

HiWi Positions

I also regularly have HiWi positions available. Currently open are:

Show selected publications only
  • Maximilian Schier, Christoph Reinders, Bodo Rosenhahn
    Learned Fourier Bases for Deep Set Feature Extractors in Automotive Reinforcement Learning
    2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), IEEE, p. to appear, September 2023
  • Maximilian Schier, Christoph Reinders, Bodo Rosenhahn
    Deep Reinforcement Learning for Autonomous Driving Using High-Level Heterogeneous Graph Representations
    2023 IEEE International Conference on Robotics and Automation (ICRA), IEEE, pp. 7147-7153, 2023
  • Maximilian Schier, Christoph Reinders, Bodo Rosenhahn
    Constrained Mean Shift Clustering
    Proceedings of the 2022 SIAM International Conference on Data Mining (SDM), SIAM, April 2022
  • Maximilian Benedikt Schier, Niclas Wüstenbecker
    Adversarial N-player Search using Locality for the Game of Battlesnake
    INFORMATIK 2019, September 2019