# CAREER: Toward Scalable and Resilient Collaborative Inference for Edge Intelligence through Network-Aware Design

> **NSF 01002627DB NSF RESEARCH & RELATED ACTIVIT** · Florida State University (FL) · $600,000

## 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 connectivity, leading to inefficient resource use and degraded inference performance when network or system conditions change. This project reconceptualizes the wireless network not merely as a communication medium, but as a coordination substrate to orchestrate model execution and resource allocation for efficient, scalable, and resilient collaborative inference. The resulting advances will support emerging applications such as mobile health, distributed robotics, and intelligent transportation systems. The project also integrates research into teaching through new courses with hands-on learning modules on edge intelligence and distributed AI. It further strengthens an existing mentoring pipeline spanning K-12 outreach, undergraduate research participation, and graduate training, preparing students for future careers across AI, systems, and networking.

The project advances the scientific foundations of network-aware collaborative inference at the intersection of networking, distributed

## Key facts

- **NSF award ID:** 2544108
- **Awardee organization:** Florida State University (FL)
- **SAM.gov UEI:** JF2BLNN4PJC3
- **PI:** Xiaonan Zhang
- **Primary program:** 01002627DB NSF RESEARCH & RELATED ACTIVIT
- **All programs:** Artificial Intelligence (AI), CAREER-Faculty Erly Career Dev, RES IN NETWORKING TECH & SYS
- **Estimated total:** $600,000
- **Funds obligated:** $374,823
- **Transaction type:** Continuing Grant
- **Period:** 07/01/2026 → 06/30/2031

## Primary source

NSF Award Search: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2544108

## Citation

> US National Science Foundation, Award 2544108, CAREER: Toward Scalable and Resilient Collaborative Inference for Edge Intelligence through Network-Aware Design. Retrieved via AI Analytics 2026-06-07 from https://api.ai-analytics.org/grant/nsf/2544108. Licensed CC0.

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