Maximilian Otte, M.Sc.

PhD Project:

Neuro-Symbolic Integration with Information Constraints

Maximilian Otte joined the Research Group in January 2025. He received his M.Sc. degree in Computer Science from TU Darmstadt in 2021, where his thesis focused on neural cellular automata. Afterward, he worked for three years at Fraunhofer in Ingolstadt on LiDAR-based smart infrastructure, highly autonomous flight, and multi-agent reinforcement learning for traffic optimization. He is currently pursuing his PhD under the supervision of Prof. Dr. Dr. Daniel Braun, studying how neural networks represent knowledge and applying these insights to bronchial carcinoma staging in PET/CT imaging.

Research Interests

• Artificial Intelligence and Machine Learning
• Neurosymbolic Artificial Intelligence
• Disentangled Representation Learning
• Causal Reasoning
• Reinforcement Learning

Publications

Pre-Print

• M. Otte, Q. Delfosse, J. Czech, and K. Kersting, ‘Generative adversarial neural cellular automata’, arXiv preprint arXiv:2108. 04328, 2021.

Peer-Reviewed

• M. Q. Mohammed, H. Meeß, and M. Otte, ‘Review of the application of quantum annealing-related technologies in transportation optimization’, Quantum Information Processing, vol. 24, no. 9, p. 296, 2025.
• R. Song et al., ‘First mile: An open innovation lab for infrastructure-assisted cooperative intelligent transportation systems’, in 2024 IEEE Intelligent Vehicles Symposium (IV), 2024, pp. 1635–1642.