Topics

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

AI Configurators; 3D Layout via Reinforcement Learning

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 through Polygonization and Polyhedralization

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

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

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 for Combinatorial Generation of Modular Designs

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

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