A Graduate Studio Guidebook for Generative Design Researchers

This document is written to guide the graduate students of design informatics, those working on Generative Design subjects

AI Configurators

AI Configurators; 3D Layout via Reinforcement Learning

Augmented Urban Planning

Developing multi-purpose Spatial Decision Support System (SDSS) or a Planning Support System (PSS) to augment the collective intelligence of the participating human actors

Combinatorial Surface & Solid Design

Combinatorial Surface & Solid Design through Polygonization and Polyhedralization

Computational Shape Optimization

Computational Shape Optimization for Designing Compression-Only Masonry/Earthy Buildings

Computational Topology Optimization

Computational Topology Optimization for Designing Compression-Only Masonry/Earthy Buildings

Digital Twins for city modeling and simulation

This research will focus on applying innovative geospatial methods, and integration of different 3D and IoT data for the creation and application of Digital Twins/3D city models

Gamification of Generative Design

Gamification of Generative Design for Combinatorial Generation of Modular Designs

Generative Configuration Design

Feed-Forward 3D Layout Optimization as to Spatial Qualities and Requirements

Generative Design for Smart Regulations

The goal is to devise a computational methodology and implement it in Python (NumPy/SciPy family of libraries)