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Research Spending & Results

Award Detail

Doing Business As Name:Vanderbilt University
  • Janos Sztipanovits
  • (615) 322-3455
  • James M Pipas
  • Douglas E Norris
  • David L Smith
  • Ethan K Jackson
Award Date:09/15/2021
Estimated Total Award Amount: $ 4,998,973
Funds Obligated to Date: $ 2,583,774
  • FY 2021=$2,583,774
Start Date:10/01/2021
End Date:09/30/2023
Transaction Type: Cooperative Agreements
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.083
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:D: Computing the Biome
Federal Award ID Number:2134862
DUNS ID:965717143
Parent DUNS ID:004413456
Program:Convergence Accelerator Resrch
Program Officer:
  • Mike Pozmantier
  • (703) 292-4475

Awardee Location

Street:Sponsored Programs Administratio
Awardee Cong. District:05

Primary Place of Performance

Organization Name:Vanderbilt University-ISIS
Street:1025 16th Avenue South Suite 102
Cong. District:05

Abstract at Time of Award

Individuals, industries, societies, and governments want to stay healthy. They need cost-effective systems to detect biological threats and predict future disease outbreaks as early as possible. COVID-19 acutely and painfully demonstrated the impacts of the unpredicted. The goals of this program, Computing the Biome, are twofold: (1) demonstrate an extensible data and AI platform that continuously monitors and predicts biothreats in a major U.S. city, and (2) create a framework for economic sustainability and global scalability of these results, by empowering businesses and advanced science missions to consume predictions and produce valuable consumer apps and breakthroughs. This team will produce and interconnect novel data streams ranging from kilometer-scale hyper-local weather, to autonomously identified disease transmitting insects (only millimeters in size), to genomically recognized known and novel viruses (only nanometers in size) – demonstrating that cross-cutting continuous data streams for biothreat detection and prediction can be rapidly unlocked. By combining their expertise in ecology, epidemiology, and virology, the team will design new predictive models and anomaly detectors. This project will develop the first of these high-impact AIs focused on predicting mosquito-borne diseases, which are difficult to control and impact over 600 million people per year. More broadly, the resulting data platform will empower development of new foundational methods for use by the AI community – based on real-world data and grounded in the societal challenges of our age. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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