APPLY HERE NOW to join 2021 VIP UrbanAI Team
Spaces are limited!
Cities have enormous potential to be sustainable hubs of vibrant activity. Investigate how big data, programming, machine learning, robots and 3D printing can optimise the design process and reduce resource use and waste at the same time.
Our cities face myriad challenges: climate change, rapid urbanisation and the integration of smart vehicles to name just a few. Our cities are also becoming ‘smarter’, and there are huge quantities of data – about population, transport, traffic and weather etc – up for grabs.
While the challenges increase the complexity of designing and operating our cities, this huge influx of data presents several exciting opportunities.
Throughout this course, we argue that data related to the built environment can provide valuable insights for urban planners, government agencies and the private sector to address challenges our cities face at present, and in the near and long-term future.
We will source data that have defined and will generate our cities and buildings (past, present and future) using web crawling, and will:
1. Clean and prepare these data for machine learning,
2. Develop and program workflows that design future cities and buildings, and
3. Feed these workflows to machines and robots to fabricate sustainable buildings.
Based on various urban and architectural challenges:
All degrees are welcome however, students specialising in the below areas are encouraged to apply.
|Desired Research Areas||Desired Skills|
Forming agile teams and using the scrum method to work together, we will develop and work on different projects. The overall agenda is to provide the foundation for a synthetic design method that combines machine learning and computational design to design sustainable and liveable cities.
Project 1. Data mining / Data cleaning
Project 2. CSS for 3D design
Project 3. Task planning for computational design tools
Project 4. Experiments in ML for Architecture and Design
Project 5. Code to Production