Presented on Energy Day (April 27) at the virtual workshop “Tackling Climate Change with Machine Learning,” held as part of the International Conference on Learning Representations (ICLR) 2020. More info at: [ Ссылка ]
Session description: The built infrastructure is a critical component of climate policies, both because of the large energy use of buildings and because of vulnerability to extreme weather events. However, access to good data about buildings can be a bottleneck in designing effective policies. Machine learning can contribute to a sustainable and resilient built infrastructure by gathering individual data on millions of buildings. This session will discuss ways to monitor infrastructure with remote sensing, and to upscale building energy use modeling to the city scale.
Speakers:
- Monika Kuffer (University of Twente)
- Nicholas Jones (World Bank)*
- Alex Nutkiewicz (Stanford)
- Sokratis Papadopoulos (New York University)
* The recording for this talk is not available; slides can be found at the workshop website ([ Ссылка ]).
