PhD and MSc Theses

PhD and MSc Theses, since 1988

Advisor DR. Michael Zibulevsky
Advisor's Email
No of theses 19
Department Computer Science
Department Web Site
Student's Name Graduation Year Degree Abstracts Research Name
Lysiansky Michael 2012 PhD Abstracts Two Dimensional Ultrasound Speckle Tracking and Inverse Acoustic Scattering Problem
Hong Tao 2021 PhD Abstracts Numerical Optimization and Multigrid Computational Methods with Applications
Osherovich Eliyahu 2012 PhD Abstracts Numerical Methods for Phase Retrieval
Shtok Joseph 2012 PhD Adaptive Reconstruction Algorithms in Computed Tomography
Begelman Grigory 2009 PhD Abstracts Processing and Interpretation of Biological Microscopical Images
Vedula Sai Sanketh 2020 MSc Learning-Based Design of Ultrasound Imaging Systems
Elbaz Dan 2018 MSc Abstracts Speech Signals Frequency Modulation Decoding via Deep Neural Networks
Senouf Ortal 2019 MSc Abstracts Improving Ultrasound Imaging with Deep Neural Networks
Boublil David 2018 MSc Abstracts Deep Learning for Inverse Problems in Image Restoration
Pfeffer Yehuda 2011 MSc Abstracts Compressive Sensing for Hyperspectral Imaging
Rubinstein Eitan 2006 MSc Abstracts Support Vector Machines via Advanced Optimization Techniques to Robust Optimization
Shwartz Sarit 2006 MSc Abstracts Blind Separation of High Dimensional Sources
Model Dmitri 2006 MSc Abstracts Multi-Sensor Signal Separation, Localization and Classification Using Nonlinear Optimization
Matalon Boaz 2006 MSc Abstracts Bayesian Methodology for Denoising Using Sparse Representations
Narkiss Guy 2006 MSc Abstracts Sequential Subspace Optimization Method for Unconstrained Optimization
Bronstein Alexander 2005 MSc Abstracts Blind Deconvolution using Relative Newton Algorithm and Learnable Sparse Representations
Polonsky Alexey 2005 MSc Abstracts EEG/MEG Source Localization Using Spatio-Temporal Sparse Representations
Cherkassky Stanislav 2004 MSc Abstracts List-Mode 3D Pet Reconstruction Using Bundle-Mirror Optimization with Subsets
Cohen Sarit 2005 MSc Abstracts Improvement of Spatial Resolution of Source Estimation of Brain Activity Using Blind Source Separation