Microsoft Research | Panel discussion and research talk: Computational advances in climate risk assessment @MicrosoftResearch | Uploaded October 2022 | Updated October 2024, 1 week ago.
Climate change poses significant risks to human welfare as well as biodiversity. Improved modeling is needed to better understand the chain of impacts, and to mitigate or avoid the worst outcomes. Microsoft and university researchers are collaborating to address this important challenge, by bringing complementary expertise to bear on critical problems. This session will feature faculty experts in carbon emissions measurement and climate risk, in conversation with Microsoft experts in the fields of causal machine learning and deep learning. Together they will address the importance and challenges of carbon accounting and climate risk prediction, and how computational approaches can improve modeling of each.
Additional Resources:
EconML -- microsoft.com/en-us/research/project/econml
DoWhy -- pypi.org/project/dowhy
ShowWhy -- github.com/microsoft/showwhy
Project Causica -- github.com/microsoft/causica
#MSFTResearchSummit
See related sessions in this track: microsoft.com/en-us/research/video/lightning-talks-sustainably-nourishing-the-world
Learn more about the 2022 Microsoft Research Summit: microsoft.com/en-us/research/event/microsoft-research-summit-2022
Climate change poses significant risks to human welfare as well as biodiversity. Improved modeling is needed to better understand the chain of impacts, and to mitigate or avoid the worst outcomes. Microsoft and university researchers are collaborating to address this important challenge, by bringing complementary expertise to bear on critical problems. This session will feature faculty experts in carbon emissions measurement and climate risk, in conversation with Microsoft experts in the fields of causal machine learning and deep learning. Together they will address the importance and challenges of carbon accounting and climate risk prediction, and how computational approaches can improve modeling of each.
Additional Resources:
EconML -- microsoft.com/en-us/research/project/econml
DoWhy -- pypi.org/project/dowhy
ShowWhy -- github.com/microsoft/showwhy
Project Causica -- github.com/microsoft/causica
#MSFTResearchSummit
See related sessions in this track: microsoft.com/en-us/research/video/lightning-talks-sustainably-nourishing-the-world
Learn more about the 2022 Microsoft Research Summit: microsoft.com/en-us/research/event/microsoft-research-summit-2022
