Davenport Selected for IEEE SPS Signal Processing Magazine Best Paper Award
Mark A. Davenport has been named as a recipient of the IEEE SPS Signal Processing Magazine Best Paper Award. Davenport and his colleagues will be recognized with this award at the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2021), currently scheduled for June 6-11 in Toronto, Ontario, Canada.
The title of Davenport’s award-winning paper is “Single-Pixel Imaging via Compressive Sampling: Building simpler, smaller, and less-expensive digital cameras.” It was published in IEEE Signal Processing Magazine in March 2008.
This paper described the “single-pixel camera,” which represented one of the first novel hardware architectures to be developed that explicitly incorporated the ideas of compressed sensing into its design. This proof-of-concept helped inspire the design of dozens–if not hundreds–of other novel sensing devices and helped to boost the profile of the ideas behind compressed sensing within the signal processing community.
Davenport is an associate professor in the Georgia Tech School of Electrical and Computer Engineering and has been on the School’s faculty since 2012. His coauthors on the paper were Marco Duarte, of the University of Massachusetts at Amherst; Dharmpal Takhar, of Shell; Jason Laska, of Lyft; Ting Sun, of Apple; and Kevin Kelly and Richard Baraniuk, both of Rice University.
IEEE Signal Processing Magazine publishes tutorial-style articles on signal processing research and applications, as well as columns and forums on issues of interest. Its coverage ranges from fundamental principles to practical implementation, reflecting the multidimensional facets of interests and concerns of the community. Its mission is to bring up-to-date, emerging, and active technical developments, issues, and events to the research, educational, and professional communities. It is also the main Society communication platform addressing important issues concerning all members.
School of Electrical and Computer Engineering
Last revised January 5, 2021