Computational and Statistical Tools to Control a Pandemic | Theoretically Speaking Series

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United States Simons Institute for the Theory of Computing
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Published on ● Video Link: https://www.youtube.com/watch?v=hnxC-9cLS3w


Duration: 1:27:02
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Peter Bartlett (Simons Institute for the Theory of Computing, moderator)

Panelists: Klaske van Heusden (University of British Columbia), Madhav Marathe (University of Virginia), Ankur Moitra (MIT), Shai Shalev-Shwartz (Hebrew University of Jerusalem), Anil Vullikanti (University of Virginia), and Bin Yu (UC Berkeley)

The ongoing COVID-19 pandemic represents an unprecedented global crisis and serves as a reminder of the social, economic, and health burden of infectious diseases. This panel discussion aims to explore the role that computational and statistical tools can play in supporting policy makers as they formulate and assess policies to control COVID-19. It brings together experts in network science, data-driven modeling, and feedback control theory to discuss how these tools might help to understand the progress of an epidemic, to forecast its future course, to infer properties of a disease, and to choose public policy responses.

https://simons.berkeley.edu/events/covid19



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Tags:
Simons Institute
Theory of Computing
Theory of Computation
Theoretical Computer Science
Computer Science
UC Berkeley
Klaske van Heusden
Madhav Marathe
Ankur Moitra
Shai Shalev-Shwartz
Anil Vullikanti
Bin Yu
Peter Bartlett
Computational and Statistical Tools to Control a Pandemic
Theoretically Speaking Series