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PhD projects

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

20152020

Research output per year

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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!

 

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Research Output

  • 6 Article
  • 4 Conference article
  • 3 Paper
  • 1 Conference contribution

Effects of spatial encoding strategies on 2D and 3D magnetic resonance fingerprinting

Cencini, M., Gomez, P., Golbabaee, M. & al, E., 2020, In : Magnetic Resonance in Medicine .

Research output: Contribution to journalConference article

Model-based super-resolution reconstruction of T2 maps

Bano, W., Piredda, G. F., Davies, M., Marshall, I., Golbabaee, M., Meuli, R., Kober, T., Thiran, J-P. & Hilbert, T., 1 Mar 2020, In : Magnetic Resonance in Medicine. 83, 3, p. 906-919 14 p.

Research output: Contribution to journalArticle

Open Access

Neural network inference for three-dimensional quantitative transient-state imaging (QTI)

Pretti, L., Cencini, M., Golbabaee, M. & et al, 2020, (Acceptance date) In : Magnetic Resonance in Medicine .

Research output: Contribution to journalConference article

CoverBLIP: accelerated and scalable iterative matched-filtering for Magnetic Resonance Fingerprint reconstruction

Golbabaee, M., Chen, Z., Wiaux, Y. & Davies, M., 3 Dec 2019, In : Inverse Problems. 36, 1, 015003.

Research output: Contribution to journalArticle

Open Access

Deep Fully Convolutional Network for MR Fingerprinting

Chen, D., Golbabaee, M., Gómez, P. A., Menzel, M. I. & Davies, M., 10 Jul 2019.

Research output: Contribution to conferencePaper

Open Access