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  Big data and machine learning for urban energy and sustainability assessment and design


   Welsh School of Architecture

   Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Urban features including façade features, window size, building age, land use, tree coverage, density are important parameters to determine urban sustainability, energy and climate performance for cities and buildings herewith in. However, it is difficult to extract such information in the real cities due to the complexity of the urban texture.

Harnessing the wealth of urban big data, from street views to satellite and infrared imagery, this PhD project aims to pioneer the use of computer vision techniques in extracting critical urban features. The objective is to provide ground-breaking analyses for urban-level sustainability and climate impact assessments.

Applicants are expected to have a very good bachelor’s or master’s degree in the subjects of architectural and urban science, environmental engineering, urban planning and design or related subject. Programming skills are preferred. Previous experience on big data and machine learning on computer vision is especially welcome. The PhD student will join a vibrant research group, comprised of leading experts in the areas of urban microclimate, architecture and urban design, computer science.

Please contact Prof Zhiwen Luo for informal enquiries. Interested applicants are encouraged to email their CV and a brief statement of purpose to Prof Zhiwen Luo ().

To apply, please complete the online application and state the project title and supervisor name.

Architecture, Building & Planning (3) Engineering (12)

Funding Notes

This PhD post is open to self-funded Home, EU and International applicants

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