Holger Giese

Prof. Dr. Holger Giese is a full Professor at the System Analysis and Modeling Group of the Hasso Plattner Institute for Digital Engineering in Potsdam, Germany. He leads research initiatives in model-driven engineering, self-adaptive systems, and cyber-physical systems, with a focus on causal representations, neuro-symbolic AI, and multi-agent reinforcement learning.

His research explores the intersection of formal modeling and machine learning, addressing challenges in:

• Runtime verification and validation of dynamic systems
• Model transformation and synchronization
• Code generation for self-optimizing architectures
• Probabilistic decision-making under uncertainty
• Transfer learning for autonomic computing

Recent work (2024-2025) emphasizes neuro-symbolic approaches for robust multi-agent systems, spatio-temporal graph modeling for cloud systems, and incremental query evaluation in dynamic environments. Collaborations span institutions like IBM Japan, Krems University, and Humboldt University.

He actively teaches courses such as Advanced Topics in Software Engineering, Graph Neural Networks, and AI Ethics Engineering, and leads labs including the Model-Driven Engineering Laboratory (MDELab.de) and Software Engineering for Self-Adaptive Systems (self-adaptive.org).