
What if predicting building energy demand did not require long simulation runs, heavy workflows, or massive datasets? Xinyue Wang recently defended her PhD, “Leveraging Machine Learning to Improve Early-stage Building Energy Optimization.” Originally trained as an architect, her research sits at the intersection of building energy simulation and machine learning. Her work focuses on making…

Complex urban simulations are often difficult to discuss collectively. Results live on individual screens, in reports, or PowerPoint presentations, making shared immersive interpretation challenging. The Research Area Sustainable Built Environments (SBE) at Chalmers developed the ACE Mixed Reality Studio to address this problem. The studio combines a physical model of the Chalmers Campus with Mixed…