CityDNN: A Deep Neural Network for Urban Energy Simulation Models | Dr. Zoltan Nagy

Presentation by Dr. Zoltan Nagy, University of Texas at Austin | The built environment is responsible for 34% of #greenhousegas #emissions. Keeping in mind that buildings and their #energysystems have a lifespan, the ability to achieve carbon #netzero goals by 2050 (or sooner) will depend on #construction and #retrofitting projects in the works right now. And this necessitates foresight by #urbanplanning experts, policymakers, #utilities, and others in designing incentives, policies, codes, and infrastructural investments. This talk describes CityDNN, a deep #neuralnetwork for urban #energysimulation models, and discusses strategies to improve these models. 0:00 - 16:42 - Presentation 16:42 - end - Audience Q&A About the Presenter: Dr. Zoltan Nagy is a roboticist turned building engineer, his research interests are in smart buildings and cities, renewable energy systems, control systems for zero emission building operation, machine learning and artificial intelligence for the built environment, complex fene