Angshul Majumdar (University of British Columbia), “A Sparsity Based Approach Towards Fast MRI Acquisition”, Advisor: Prof. Rabab K. Ward, 2012 Magnetic Resonance Imaging (MRI) is a safe medical imaging modality that can acquire high quality scans. However, MRI has a relatively long acquisition time. Reducing the MRI data acquisition time had been a challenge to researchers for the last two decades. In this thesis, the author proposed Compressed Sensing based techniques to speed-up MRI scans. The main contributions of this thesis are the following: 1. Novel algorithms for static MRI reconstruction using sparsity and rank-deficiency of images. 2. New formulations for jointly recovering multi-echo images. 3. Robust techniques for multi-coil parallel MRI reconstructions which do not require any explicit or implicit information about sensitivity profiles of the coils. 4. Near real-time reconstruction algorithms for dynamic MRI reconstruction; thus paving ways for image-guided surgery and monitoring applications. For more details, please read the full thesis or contact the author.