Chen To Receive NSF CAREER Award
Xiang Chen, Assistant Professor, Electrical and Computer Engineering (ECE), is set to receive funding from the National Science Foundation for the project: "CAREER: 'Adapt, Learn, Collaborate' — Closing the Pervasive Edge AI."
A huge conflict emerged regarding the AI designs between hardware-oriented customization and data-oriented uniformity.
This project targets a modularized deep neural network generation and deployment framework to accommodate these two distinct needs. Through dedicated system resource analysis, structural design, and composite training, Chen will propose a set of universal principal modules to be selectively combined into different model structures for heterogeneous edge devices without additional tuning efforts.
At the same time, Chen will consider cross-module correlations and cross-model collaboration for novel cooperation schemes to build pervasive edge intelligence connections. Such a framework is referred to as "liquid intelligence" to highlight its hardware-aware adaptability and edge continuous generality.
By reducing the edge AI design and optimization cost, this project also looks ahead to particular system implementation details and practical application integration such as connected autonomous driving systems, demonstrating the framework potential in terms of computing and communication efficiency, convergence accuracy, and edge privacy.
Chen will receive total funding of $580,000 from the National Science Foundation for this award. Funding will begin in July 2022 and will end in late June 2027.
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