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Ulugbek S. Kamilov

Research Scientist

Multimedia Group
Mitsubishi Electric Research Laboratories

201 Broadway, 8th Floor
Cambridge, MA 02139, USA

News

September 2016: The manuscript "Inference for Generalized Linear Models via Alternating Directions and Bethe Free Energy Minimization" was accepted to IEEE Transactions on Information Theory.

August 2016: The special sessing proposal for ICASSP 2017 on "Large-Scale Computational Imaging with Wave Models" was accepted. The session is organized jointly with Laura Waller and Brendt Wohlberg.

August 2016: Delivered two keynote talks at iTWIST 2016: "Learning MMSE Optimal Thresholds for FISTA" and "Minimizing Isotropic Total Variation without Subiterations."

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Biography

Ulugbek S. Kamilov is a Research Scientist in the Computational Sensing Team at Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA. Dr. Kamilov obtained his B.Sc. and M.Sc. in Communication Systems, and Ph.D. in Electrical Engineering from the École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, in 2008, 2011, and 2015, respectively. In 2007, he was an Exchange Student at Carnegie Mellon University (CMU), Pittsburgh, PA, USA, in 2010, a Visiting Student at Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, and in 2013, a Visiting Student Researcher at Stanford University, Stanford, CA, USA.

Dr. Kamilov's research focus is computational imaging and sensing with an emphasis on the development and analysis of large-scale computational techniques for applications in biomedical and industrial imaging. His research interests cover signal processing aspects of multimodal sensor fusion, tomographic imaging, machine learning, through-the-wall imaging, and distributed sensing. He has co-authored 14 journal and 27 conference publications in these areas. His Ph.D. thesis work on Learning Tomography (LT) was selected as a finalist for EPFL Doctorate Awards 2016 and was featured in the "News and Views" section of the Nature magazine. Since 2016, Dr. Kamilov is a member IEEE Special Interest Group on Computational Imaging.

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