CAREER: Toward Scalable and Resilient Collaborative Inference for Edge Intelligence throug — NSF Award to Florida State University
Collaborative inference at the network edge enables low-latency and privacy-sensitive artificial intelligence (AI) services without relying on remote cloud infrastructure. Distributing increasingly complex neural network models across nearby edge devices enables the pooling of their compute and memory resources to perf
| Award title | CAREER: Toward Scalable and Resilient Collaborative Inference for Edge Intelligence throug |
|---|---|
| Award ID | 2544108 |
| Awardee | Florida State University |
| City | TALLAHASSEE |
| State | FL |
| Amount obligated | $374,823 |
| Principal investigator | Xiaonan Zhang |
| Program | Networking Technology and Syst |
| Start date | 07/01/2026 |
| Abstract | Collaborative inference at the network edge enables low-latency and privacy-sensitive artificial intelligence (AI) services without relying on remote cloud infrastructure. Distributing increasingly complex neural network models across nearby edge devices enables the pooling of their compute and memory resources to perform inference beyond the capability of any single device. Existing collaborative inference approaches rely on centralized or static control under assumptions of stable network conn |
| Source | NSF Awards |
$799/mo
Try NSFGrants →