Ulugbek S. Kamilov

Research Scientist

Computational Sensing
Mitsubishi Electric Research Laboratories (MERL)

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


June 2017: I am happy to announce that I will be starting as an Assistant Professor at the Washington University this fall, to continue my work on computational imaging and sensing. I see this appointment as a natural next challenge and an opportunity for professional growth.

June 2017: Invited talk at OSA Mathematics in Imaging Meeting in San Francisco, CA, USA (26 June 2017 at 4:15 PM).

June 2017: Our accepted ICIP 2017 manuscript is now online "Online Convolutional Dictionary Learning for Multimodal Imaging."

May 2016: Three interns joined the Computational Sensing team at MERL: Yanting Ma from North Carolina State University (NCSU), Bihan Wen from UIUC, and Rakshith Srinivasa from Georgia Tech. Welcome!

May 2017: New preprint "SEAGLE: Sparsity-Driven Image Reconstruction under Multiple Scattering".

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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 is a member IEEE Special Interest Group on Computational Imaging since January 2016.

Dr. Kamilov's research focus is computational imaging with an emphasis on the development and analysis of large-scale computational techniques for biomedical and industrial applications. His research interests cover imaging through scattering media, multimodal imaging, distributed radar sensing, and through-the-wall imaging. He has co-authored 17 journal and 36 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.

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