Agentic Systems – AI-Based Configuration of Modular Architecture

This thesis explores how AI agents can support the design, variation, and organization of modular components.

Theme:		AI-driven configurators offer new opportunities for modular and adaptive architectural systems. This thesis explores how AI agents can support the design, variation, and organization of modular components in response to different spatial and functional requirements. The focus lies on the co-creative interaction between designers and AI systems in shaping adaptable architectural typologies. The TUM Main Campus rooftop serves as one possible scenario to test the configurator, but the system should remain applicable to a wide range of contexts.
Goal:		The goal is to develop a digital configurator that enables the generation and variation of modular architectural elements through AI-supported decision-making. Emphasis is placed on human-AI collaboration, design logic, and flexibility across different implementation contexts.
Preferred background:		Computational Design, Master of Architecture, Media Informatics LMU
Requirements:		Scripting, Parametric design workflows (e.g., Rhino + Grasshopper), AI-assisted spatial generation, critical reflection on human-AI interaction in design processes
Contact:		Clemens Lindner (clemens.lindner(at)zaha-hadid.com) Christoph Geiger (christoph.geiger(at)zaha-hadid.com)