Dr. Li’'s research encompasses the fields of Signal Processing and Wireless Communications and Networking.
He is currently researching ways to develop an integrated framework for wireless sensor networks. A recently received NSF grant, entitled “Data-Driven Adaptive Quantization for Distributed Inference,” addresses a fundamental challenge of quantization for distributed inference in a sensor network environment, where the optimum quantizer generally cannot be implemented due to its dependence on unknown parameters associated with the random events being monitored by the sensor network.
His goal is to develop new sensing and inference techniques by exploiting learning and collaboration among sensor nodes. These techniques will afford improved awareness of the dynamically changing environment in a cognitive network.
The research being conducted by Dr. Li has the potential to solve several important distributed inference problems with bandwidth and power constraints, further advancing research and development of wireless sensor networks that are expected to have significant economic and social impact.
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