What is "Risk" Anyway? Using Machine Learning to Quantify Weather Risk
Talk by Hillary Scannell on using ML to quantify climate-driven weather risks and apply models to decision making
Hello Boulder WiMLDS! We have another great talk slated for our next meeting!
Hillary Scannell is a Senior Data Scientist at Jupiter Intelligence, where she develops machine learning and data-driven methods for quantifying exposure to extreme weather risks, including floods, heat waves, and wildfires.
In this talk, Hillary will explore how machine learning is used to characterize risk in a changing climate, including how likely extremes are, how severe they might become, and how we can represent what we do not know with honesty and rigor. Using wildfire as a guiding example, she'll walk through how these models are built and applied in practice and what becomes challenging when ML moves from research into real-world decision-making. This includes reasoning under uncertainty, building systems people can trust, and connecting climate information to planning across finance and infrastructure.
6:00 Meet and greet 6:15 Presentation Networking to follow. Light snacks will be provided.
Please RSVP even if you can't make it if you would like to continue receiving event notifications as we are no longer using Meetup.
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