Project titles and description:

1. Graph Machine Learning in Architecture Discipline

This project explores the use of graph machine learning (GML) to represent and analyze architectural systems as interconnected networks. Students will work on transforming building data into graph structures to study spatial relationships, topology, and performance. The project aims to develop predictive models for applications such as energy efficiency and design optimization. Participants will gain experience in Python-based workflows and AI-driven architectural analysis.

2. Robotic Assembly in Architecture

This project investigates the use of robotics in architectural fabrication and construction processes. Students will explore robotic workflows for assembling modular components, focusing on precision, efficiency, and design flexibility. The research includes hands-on experimentation with robotic arms and digital fabrication tools. The goal is to understand how robotics can transform construction methods and enable innovative architectural solutions.

3. 3D Concrete / Earth Material Printing Using Industrial 3D Printers

This project focuses on large-scale additive manufacturing using concrete and earth-based materials. Students will study material behavior, printing parameters, and structural performance of 3D-printed elements. The research aims to explore sustainable construction techniques suitable for local climates. Participants will gain practical experience in digital fabrication and emerging construction technologies.