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eess.SY2026
CREST: Deployment-Realistic Hardware-in-the-Loop NAS for Embedded Sensing Systems
Joseph Q. Zales, Pragya Sharma, Mani Srivastava
Deploying neural networks on low-power microcontrollers (MCUs) requires selecting model architectures under tight memory, latency, and energy constraints. Existing workflows often…
eess.SY2026
FM-CAC: Carbon-Aware Control for Battery-Buffered Edge AI via Time-Series Foundation Models
Kang Yang, Walid A. Hanafy, Prashant Shenoy +1
As edge AI deployments scale to billions of devices running always-on, real-time compound AI pipelines, they represent a massive and largely unmanaged source of energy consumption…