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My research interests include areas at the intersection of inverse problems, statistical signal processing, machine learning, and optimization. More recently, I have been working on the applications of deep learning for solving inverse problems that frequently arise in medical imaging applications such as computed tomography, magnetic resonance imaging, etc. I take interest in designing novel deep neural network architectures and learning strategies that are particularly suited for image reconstruction problems. Although I primarily focus on medical imaging applications, the learning paradigms I develop often transcend the application at hand and apply to more general computer vision tasks. I am also keenly interested in developing robust and scalable optimization algorithms with theoretical guarantees for high-dimensional signal estimation problems with structural constraints such as sparsity and low-rank.

The list of publications on this page is automatically updated and is incomplete. Please visit my Google Scholar profile to view all my published papers and preprints. 


Phase Retrieval From Binary Measurements
S Mukherjee, CS Seelamantula
– IEEE Signal Processing Letters

Research Group

Cambridge Image Analysis




01223 337889