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> Machine learning for medical imaging > Compressed sensing theory > Stochastic optimisation for large-scale machine learning

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Personal profile

Research interests

Mohammad received his Ph.D. degree (2012) in Computer and Communication Sciences from the École Polytechnique Fédérale de Lausanne (EPFL) , Switzerland. His Ph.D. thesis focused on compressed sensing and source separation strategies for multichannel data. He was a CNRS postdoctoral researcher in Applied Mathematics Research Centre (CEREMADE) at Université Paris Dauphine, France, in 2013. He was awarded the Swiss National Science Foundation (SNSF) Fellowship and visited the DSP group at Rice University, Houston TX USA, in 2014. In 2015, he joined the School of Engineering at the University of Edinburgh as an EPSRC Research Associate and held an early career award from the Scottish Research Partnership in Engineering (SRPe) for the project “Accelerating quantitative Magnetic Resonance Imaging acquisition and reconstruction”. Since August 2018, Mohammad joined the University of Bath as an assistant professor (lecturer) in Computer Science.

His research interests include machine learning, signal and image processing, compressed sensing, low-complexity data models, source separation, optimisation algorithms for large-scale machine learning and data science: theoretical and applied to medical imaging and computer vision.

For more information please visit my personal webpage!

 

External positions

Visiting researcher , University of Edinburgh

1 Aug 2018 → …

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