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COVID Information Commons Research Lightning Talks Webinar: May 19, 2021 - 4-5pm ET

Dear Researchers and Students,

Join us on May 19 at 4-5pm ET for the next COVID Information Commons research lightning talks webinar! Develop new insights and potentially new collaborations to tackle the COVID-19 pandemic. Five NSF funded researchers will share their research focus and findings, and answer questions from the community. We hope to see you there! A list of speakers is below…

The COVID Information Commons (CIC) is an open website (https://covidinfocommons.net) for researchers, students and decision-makers from academia, government, nonprofit, and industry to identify collaboration opportunities, to leverage each other’s research findings, and to accelerate the most promising research to mitigate the broad societal impacts of the COVID-19 pandemic. The CIC launched in July 2020 as an NSF-funded project led by the Northeast Big Data Innovation Hub hosted by Columbia University, in collaboration with the Midwest Big Data Innovation Hub, South Big Data Innovation Hub, and West Big Data Innovation Hub.

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May 2021 Speakers:

Alka Sapat, Florida Atlantic University: RAPID: Health, Housing, and Hazards: COVID-19, Subjective Resilience, Vulnerabilities, and Policy Evolution in Hurricane Prone Counties. Funded by NSF Social, Behavioral and Economic Sciences / Division of Social and Economic Sciences.

Ruth Serra-Moreno, University of Rochester: Membrane remodeling dynamics by SARS-CoV-2. Funded by NSF Biological Sciences / Division of Molecular and Cellular Biosciences.

David Konisky, Indiana University: The Effects of COVID-19 on Household Energy Insecurity. Funded by NSF Social, Behavioral and Economic Sciences / Division of Social and Economic Sciences.

Austin Mast, Florida State University: Rapid Creation of a Data Product for the World’s Specimens of Horseshoe Bats and Relatives, a Known Reservoir for Coronaviruses. Funded by NSF Biological Sciences / Division of Biological Infrastructure.

Peter Pirolli, Florida Institute for Human and Machine Cognition, Inc.: Improving Computational Epidemiology with Higher Fidelity Models of Human Behavior. NSF Computer and Information Science and Engineering / Division of Information and Intelligent Systems.

Watch previous COVID lightning talks on the CIC Meet the Researchers page.
https://covidinfocommons.datascience.columbia.edu/content/meet-researchers

Best,
Florence D. Hudson
coPI – COVID Information Commons (NSF #2028999)
Executive Director, Northeast Big Data Innovation Hub

Columbia University
fh2417@columbia.edu

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