Mitsubishi Electric Research Laboratories
201 Broadway, 8th Floor
Cambridge, MA 02139
February 2015: Our manuscript "A Learning Approach to Optical Tomography" is now available online. It was co-authored with Morteza Shoreh, Dr. Ioannis Papadoupoulos, Dr. Alexandre Goy, Dr. Cedric Vonesch, Prof. Michael Unser, and Prof. Demetri Psaltis.
January 2015: Our manuscript "Inference for Generalized Linear Models via Alternating Directions and Bethe Free Energy Minimization" is now available online. It was co-authored with Prof. Sundeep Rangan, Prof. Alyson Fletcher, and Prof. Phil Schniter.
January 2015: I am pleased to announce that I will be joining Mitsubishi Electric Research Laboratories (MERL), Cambridge, USA, starting from February 2015. I will be a member of Multimedia group that specializes in the development of efficient solutions for the acquisition, representation, and processing of multimedia.
Ulugbek Kamilov received his PhD degree in Electrical Engineering from the École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, in 2015.
In 2007-08, he was an exchange student in Electrical and Computer Engineering at Carnegie Mellon University. In 2008, he worked as a research intern at the Telecommunications Research Center in Vienna, Austria. In 2009, he worked as a software engineering intern at Microsoft. In 2010-11, he was a visiting student in the Research Laboratory of Electronics at Massachusetts Institute of Technology (MIT). In 2013, he was a visiting student researcher in the Information Systems Laboratory at Stanford University.
Since February 2015, he is with the Multimedia Group at MERL. His research interest lies in the development of advanced algorithms for solving inverse problems.
I develop statistical models and algorithms for the reconstruction of biomedical images from highly undersampled or distorted measurements. Such problems are common in various image acquisition modalities such as tomography, magnitic resonance, bio-microscopy, astronomy, etc.
I am interested in the development of iterative algorithms that allow to perform inference on large dimensional data in an efficient way. In particular, message-passing algorithms on graphical models are of high interest to me at the moment.
My full CV can be found [here]. For my LinkedIn go here .
Google Scholar profile: [here]. Researcher ID profile:
M. H. Shoreh, U. S. Kamilov, I. N. Papadopoulos, A. Goy, C. Vonesch, M. Unser, and D. Psaltis, "A Learning Approach to Optical Tomography," arXiv:1502.01914 [physics.optics], February 2015. [arXiv]
S. Rangan, A. K. Fletcher, P. Schniter, and U. S. Kamilov, "Inference for Generalized Linear Models via Alternating Directions and Bethe Free Energy Minimization," arXiv:1501.01797 [cs.IT], January 2015. [arXiv]
U. S. Kamilov, E. Bostan, and M. Unser, "Variational Justification of Cycle Spinning for Wavelet-Based Solutions of Inverse Problems," IEEE Signal Process. Letters., vol. 21, no. 11, pp. 1326-1330, November 2014. [link]
U. S. Kamilov, S. Rangan, A. K. Fletcher, and M. Unser, "Approximate Message Passing with Consistent Parameter Estimation and Applications to Sparse Learning," IEEE Trans. Inf. Theory., vol. 60, no. 5, pp. 2969-2985, May 2014. [link] [nips] [arXiv] [code]
U. S. Kamilov, V. K. Goyal, and S. Rangan, "Message-Passing De-Quantization with Applications to Compressed Sensing," IEEE Trans. Signal Process., vol. 60, no. 12, pp. 6270-6281, December 2012. [link] [isit] [arXiv] [gamp]
U. S. Kamilov, E. Bostan, and M. Unser, "Wavelet Shrinkage with Consistent Cycle Spinning Generalizes Total Variation Denoising," IEEE Signal Process. Letters, vol. 19, no. 4, pp. 187-190, April 2012. [link] [supplement] [code]