An assistant professor in the Georgia Tech School of Electrical and Computer Engineering (ECE), Davenport and his coauthors will be presented with this honor at the IEEE International Conference on Acoustics, Speech, and Signal Processing, scheduled for March 20-25, 2016 in Shanghai, China.

Davenport and his coauthors Richard Baraniuk (Rice University), Petros Boufounos (Mitsubishi Electric Research Labs), and Michael Wakin (Colorado School of Mines) will receive this award for their paper entitled “Signal Processing with Compressive Measurements,” which was published in the IEEE Journal of Selected Topics in Signal Processing, vol. 4, no. 2, April 2010.

In recent years, a robust theory of "compressive sensing" has been developed that demonstrates the potential for certain randomized measurement schemes to efficiently acquire structured signals (where the number of measurements can be much smaller than the number of Nyquist-rate samples). This has inspired the design of hardware systems that directly implement random measurement protocols. This paper develops methods to solve a range of classical signal processing problems—such as detection, classification, estimation, and filtering—using the kind of compressive measurements generated by such hardware architectures without ever reconstructing the signals involved.