Mitsubishi Electric Research Laboratories
201 Broadway, 8th Floor
Cambridge, MA 02139
January 2015: Our manuscript "Optical tomographic image reconstruction based on beam propagation and sparse regularization" was accepted to IEEE Transactions on Computational Imaging. It was co-authored with Dr. Ioannis Papadoupoulos, Morteza Shoreh, Dr. Alexandre Goy, Dr. Cedric Vonesch, Prof. Michael Unser, and Prof. Demetri Psaltis.
December 2015: New internship openning "MM930: Inverse Scattering" at MERL. Join a research team in Cambridge, MA, USA, to develop novel methods for computational inverse scattering. Publication of the results produced during the internship is expected.
December 2015: Recent manuscript "Learning optimal nonlinearities for iterative thresholding algorithms" is now available online. The manuscript was co-authored with Dr. Hassan Mansour.
Ulugbek Kamilov obtained his PhD in Electrical Engineering from the École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, in 2015.
Ulugbek's PhD research developed computational estimation techniques for solving imaging inverse problems, in particular for biomicroscopy. His interests include signal acquisition and processing, signal representation, computational sensing and imaging, and resolution of inverse problems. Prior to joining to MERL in 2015, Ulugbek was an exchange student at Carnegie Mellon University in 2007, a visiting student at MIT in 2010, and a visiting student researcher at Stanford University in 2013.
I develop new methods for computational resolution of imaging inverse problems. Specifically, my work covers three areas: (a) study of the physical measuremnt processes; (b) design of an inference algorithm that can turn the measurements into the desired image; (c) theoretical analysis of the algorithms. My work has been directly applied to various acquisition modalities such as optical tomographic microscopy, magnitic resonance imaging, radar, etc.
I continuously study various tools that would allow me to perform inference on large dimensional data in a more efficient way. In particular, probabilistic inference algorithms, machine learning techniques, and optimization methods are of high interest to me.
U. S. Kamilov, I. N. Papadopoulos, M. H. Shoreh, A. Goy, C. Vonesch, M. Unser, and D. Psaltis, "Optical tomographic image reconstruction based on beam propagation and sparse regularization," IEEE Trans. Comput. Imag., in press. [link]
U. S. Kamilov, I. N. Papadopoulos, M. H. Shoreh, D. Psaltis, and M. Unser, "Isotropic inverse-problem approach for two-dimensional phase unwrapping," J. Opt. Soc. Am. A, vol. 32, no. 6, pp. 1092-1100, June 2015. [link] [arXiv] [code]
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]