Justin Romberg


Justin Romberg

Dr. Justin Romberg is a professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. Dr. Romberg received the B.S.E.E. (1997), M.S. (1999) and Ph.D. (2004) degrees from Rice University in Houston, Texas. From fall 2003 until fall 2006, he was a Postdoctoral Scholar in Applied and Computational Mathematics at the California Institute of Technology. He spent the summer of 2000 as a researcher at Xerox PARC, the fall of 2003 as a visitor at the Laboratoire Jacques-Louis Lions in Paris, and the fall of 2004 as a Fellow at UCLA's Institute for Pure and Applied Mathematics. In fall 2006, he joined the ECE faculty as a member of the Center for Signal and Image Processing. In 2008, he received an ONR Young Investigator Award, in 2009 he received a PECASE award and a Packard Fellowship, and in 2010 he was named a Rice University Outstanding Young Engineering Alumnus. In 2006-2007, he was a consultant for the TV show "Numb3rs," and from 2008-2011, he was an Associate Editor for the IEEE Transactions on Information Theory.


  1. M. Davenport and J. Romberg, "An Overview of Low-Rank Matrix Recovery from Incomplete Observations," Journal on Special Topics in Signal Processing, vol. 10, no. 4, pp. 608–622, 2016.
  2. W. Mantzel and J. Romberg, "Compressed Subspace Matching on the Continuum," Information and Inference, vol. 4, no. 2, pp. 79–107, 2015.
  3. Balavoine, J. Romberg, and C. Rozell, "Discrete and continuous iterative soft thresholding with a dynamic input," IEEE Transactions on Signal Processing, vol. 63, no. 12, pp. 3165–3176, 2015.
  4. Ahmed, B. Recht, and J. Romberg, "Blind deconvolution using convex program- ming," IEEE Trans. Information Theory, vol. 60, no. 3, pp. 1711-1732, 2014.
  5. M. Asif and J. Romberg, "Dynamic updating for £1 minimization," IEEE Journal on Special Topics in Signal Processing, vol. 4, pp. 421434, April 2010.
  6. J. Romberg, "Compressive sensing by random convolution," SIAM J. Imaging Science, vol. 2, pp. 1098–1128, 2009.
  7. H. Rauhut, J. Romberg, and J. Tropp, "Restricted isometries for partial circulant Matrices," Applied and Computational Harmonic Analysis, vol. 32, no. 2, pp. 242254, February 2012.
  8. E. Candes and J. Romberg, "Sparsity and incoherence in compressive sampling," In- verse Problems, vol. 23, pp. 969-986, June 2007.
  9. E. Candes, J. Romberg, and T. Tao, "Robust uncertainty principles: Exact signal re- construction from highly incomplete frequency information," IEEE Trans. Information Theory, vol. 52, pp. 489-509, February 2006.

Justin Romberg


Justin Romberg

Dr. Justin Romberg is a professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. Dr. Romberg received the B.S.E.E. (1997), M.S. (1999) and Ph.D. (2004) degrees from Rice University in Houston, Texas. From fall 2003 until fall 2006, he was a Postdoctoral Scholar in Applied and Computational Mathematics at the California Institute of Technology. He spent the summer of 2000 as a researcher at Xerox PARC, the fall of 2003 as a visitor at the Laboratoire Jacques-Louis Lions in Paris, and the fall of 2004 as a Fellow at UCLA's Institute for Pure and Applied Mathematics. In fall 2006, he joined the ECE faculty as a member of the Center for Signal and Image Processing. In 2008, he received an ONR Young Investigator Award, in 2009 he received a PECASE award and a Packard Fellowship, and in 2010 he was named a Rice University Outstanding Young Engineering Alumnus. In 2006-2007, he was a consultant for the TV show "Numb3rs," and from 2008-2011, he was an Associate Editor for the IEEE Transactions on Information Theory.


  1. M. Davenport and J. Romberg, "An Overview of Low-Rank Matrix Recovery from Incomplete Observations," Journal on Special Topics in Signal Processing, vol. 10, no. 4, pp. 608–622, 2016.
  2. W. Mantzel and J. Romberg, "Compressed Subspace Matching on the Continuum," Information and Inference, vol. 4, no. 2, pp. 79–107, 2015.
  3. Balavoine, J. Romberg, and C. Rozell, "Discrete and continuous iterative soft thresholding with a dynamic input," IEEE Transactions on Signal Processing, vol. 63, no. 12, pp. 3165–3176, 2015.
  4. Ahmed, B. Recht, and J. Romberg, "Blind deconvolution using convex program- ming," IEEE Trans. Information Theory, vol. 60, no. 3, pp. 1711-1732, 2014.
  5. M. Asif and J. Romberg, "Dynamic updating for £1 minimization," IEEE Journal on Special Topics in Signal Processing, vol. 4, pp. 421434, April 2010.
  6. J. Romberg, "Compressive sensing by random convolution," SIAM J. Imaging Science, vol. 2, pp. 1098–1128, 2009.
  7. H. Rauhut, J. Romberg, and J. Tropp, "Restricted isometries for partial circulant Matrices," Applied and Computational Harmonic Analysis, vol. 32, no. 2, pp. 242254, February 2012.
  8. E. Candes and J. Romberg, "Sparsity and incoherence in compressive sampling," In- verse Problems, vol. 23, pp. 969-986, June 2007.
  9. E. Candes, J. Romberg, and T. Tao, "Robust uncertainty principles: Exact signal re- construction from highly incomplete frequency information," IEEE Trans. Information Theory, vol. 52, pp. 489-509, February 2006.