Sponsored by the IEEE Circuits and Systems Society and the IEEE Signal Processing Society


For contributions to the foundations of statistical signal processing with applications to distributed sensing and performance benchmarking

The statistical signal processing algorithms and numerical optimization methods pioneered by Alfred O. Hero, III have become essential components of sensor networks important to the development of the Internet of Things and have led to advances in medical imaging, wireless communications, multiagent distributed systems, and deep learning applications. His work on signal processing for distributed self-calibration and tracking in sensor networks has driven the explosion in wireless network localization technology and its applications to data-in-motion, personalized health, security, inventory control, and environmental monitoring. His development of the space-alternating generalized expectation-maximization (SAGE) algorithm has improved medical image reconstruction, and his averaged incremental gradient (AIG) algorithm has impacted tomographic imaging as well as machine learning.

An IEEE Fellow, Hero is the John H. Holland Distinguished University Professor of Electrical Engineering and Computer Science at the University of Michigan, Ann Arbor, MI, USA.

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