# Romberg

### From Wikimization

Current revision (22:34, 4 December 2011) (edit) (undo) (→[http://users.ece.gatech.edu/~justin/ECE-6250-Fall-2007/Course_Notes.html Course Notes for ECE 6250], Advanced Topics in Digital Signal Processing, Fall 2007, Georgia Tech) |
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[http://users.ece.gatech.edu/~justin/ssp2007/ssp07-cs-tutorial.pdf by Justin Romberg & Michael Wakin presented at IEEE 14th Workshop on Statistical Signal Processing, Madison Wisconsin, August 26, 2007] | [http://users.ece.gatech.edu/~justin/ssp2007/ssp07-cs-tutorial.pdf by Justin Romberg & Michael Wakin presented at IEEE 14th Workshop on Statistical Signal Processing, Madison Wisconsin, August 26, 2007] | ||

- | ==[http://users.ece.gatech.edu/~justin/ECE-6250-Fall- | + | ==[http://users.ece.gatech.edu/~justin/ECE-6250-Fall-2011/styled/index.html Course Notes for ECE 6250], Advanced Topics in Digital Signal Processing, Fall 2011, Georgia Tech== |

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## Current revision

# JUSTIN ROMBERG

Justin Romberg received the BS (1997), MS (1999), and PhD (2003) degrees in Electrical and Computer Engineering from Rice University. Romberg co-authored many publications with Prof. Richard Baraniuk at Rice, and was a Texas Instruments Distinguished Graduate Fellow. Romberg spent Fall 2003 as visitor at Laboratoire Jacques-Louis Lions at Paris VI, and Fall 2004 as visiting Fellow at UCLA's Institute for Pure and Applied Mathematics. He was a Postdoctoral Scholar in Applied and Computational Mathematics at Caltech from 2003 until 2006. He joined Georgia Institute of Technology in 2006 as Assistant Professor in the School of Electrical and Computer Engineering.

Justin Romberg won the Office of Naval Research Young Investigator Award in 2008
for his proposal “Compressive Sampling for Next-Generation Signal Acquisition".
Dr. Romberg's research focuses on mathematics of data acquisition.
He is interested in how randomness increases efficiency in data acquisition, in particular, reducing both cost and computational complexity of high-resolution sensing systems.
This work will influence the design of next-generation analog-to-digital converters, radar imaging platforms, and Magnetic Resonance Imaging (MRI) systems.