Abstract & Details
Description
Award ID: 2134862
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.
NSF Program Director: Michael Reksulak
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.
NSF Program Director: Michael Reksulak
| Status | Closed |
|---|---|
| Effective start/end date | 10/01/21 → 09/30/25 |
Lead and Sub-Awardee Organization(s)
Funding
- Other Programs (Technology): $4,998,973.00
Active Fiscal Year
- FY2024
- FY2023
- FY2022
- FY2025
Start Fiscal Year
- FY2022
TIP Programs
- Other Programs (Technology)
Key Technology Areas
- Artificial Intelligence
- (confidence score: 100%)
- Biotechnology
- (confidence score: 100%)
- Data and Cybersecurity
- (confidence score: 100%)
- Disaster Prevention and Mitigation
- (confidence score: 100%)
Technology Foci
- Data Management / Databases
- (confidence score: 99%)
- Genomics and bioinformatics
- (confidence score: 100%)
- Pandemic prevention and response
- (confidence score: 99%)
- Artificial Intelligence (Broad)
- (confidence score: 100%)
Congressional District at Award
- District n. 05 of Tennessee
Current Congressional District
- District n. 07 of Tennessee
United States
- Tennessee
Core Based Statistical Area (CBSA)
- Nashville-Davidson--Murfreesboro--Franklin, TN
County
- County: Davidson, TN
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint. Learn more about Elsevier's Fingerprint Engine here: https://beta.elsevier.com/products/elsevier-fingerprint-engine