This repository contains materials for my Xinyue Wang’s research on creating machine learning models to predict residential building energy demand from early-stage architectural design variables.
Research focus
The PhD project investigates how simple architectural design variables (shape, orientation, glazing ratio, building compactness, etc.) influence annual energy demand. The goal is to produce fast, accurate surrogate models that can be used during early design exploration to estimate heating and cooling loads without running costly simulations.