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Risky Science Podcast
Risk Market News
20 episodes
1 week ago
The Risky Science Podcast features conversations with scientists, insurers, investors, portfolio managers, and others about the evolving science of predicting and modeling risk across both natural and man-made perils.
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Investing
Business,
Science
RSS
All content for Risky Science Podcast is the property of Risk Market News and is served directly from their servers with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
The Risky Science Podcast features conversations with scientists, insurers, investors, portfolio managers, and others about the evolving science of predicting and modeling risk across both natural and man-made perils.
Show more...
Investing
Business,
Science
https://is1-ssl.mzstatic.com/image/thumb/Podcasts221/v4/65/5f/95/655f9531-df9c-8a7b-8b7c-0ef891c00c66/mza_3849630888331190042.jpg/600x600bb.jpg
Multi-Hazard Modeling, AI, and the Future of Risk With Paolo Bocchini
Risky Science Podcast
41 minutes
4 months ago
Multi-Hazard Modeling, AI, and the Future of Risk With Paolo Bocchini

We're joined by Dr. Paolo Bocchini, Professor of Civil and Environmental Engineering at Lehigh University, a leading researcher  in catastrophe modeling and infrastructure resilience. Dr. Bocchini is the director of Lehigh’s Center for Catastrophe Modeling and Resilience, and he’s spearheading a new collaboration with Rice University—the Consortium for Enhanced Resilience and Catastrophe Modeling.


In this episode, we dive into why academic and private-sector research in catastrophe risk have grown apart—and what it takes to reconnect them. We talk about multi-hazard risk, the power and limits of AI in modeling, the role of surrogate models, and how future disasters—from wildfires to earthquakes—demand new thinking.


Risky Science Podcast
The Risky Science Podcast features conversations with scientists, insurers, investors, portfolio managers, and others about the evolving science of predicting and modeling risk across both natural and man-made perils.