Assistant Professor (Lecturer)
Computer Science Department
The University of Bath
E-mail: m [dot] golbabaee [at] bath.ac.uk
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.
I am always looking for highly motivated PhD students to work on topics related to:
- Machine learning for medical imaging
- Compressed sensing theory
- Stochastic optimisation for large-scale machine learning
HIRING! Applications are invited for a funded PhD studentship on Optimisation for large-scale machine Learning (starting fall 2021)
NEWS (14.10.2020): congratulations Billy (Junqi) for his IEEE Transactions on Computational Imaging paper "The practicality of stochastic optimisation in imaging inverse problems". Read more about it here. NEWS (23.06.2020): Accepted paper at MICCAI 2020. read more about "Compressive MR Fingerprinting reconstruction with neural proximal gradient iterations" here. NEWS (10.06.2020): Accepted paper at Nature Scientific Reports on "Rapid three-dimensional multiparametric MRI with quantitative transient-state imaging" read more about it here. NEWS (15.05.2020): Three papers accepted at ISMRM 2020 on quantitative prostate and brain MR Imaging, great collaborations with Institute for Cancer Research, TU Munich, U Pisa, and GE Healthcare. NEWS (23.01.2020): Compressive MRI quantification with convex priors and deep auto-encoders, read more here! NEWS (10.10.2019): CoverBLIP acceleration for MR Fingerprinting is published. Find related codes and demos here! NEWS (15.08.2019): Congratulation Wajiha on her MRM paper about MRI super-resolution! NEWS (24.06.2019): My invited talk at Mathematics in Imagining, OSA's Imaging and Applied Optics Congress. NEWS (06.05.2019): "Magna Cum Laude Award" of the ISMRM 2019 for our work on T2 mapping super-resolution! Many congrats to Wajiha Bano and collaborators from the University of Edinburgh, EPFL and Siemens Healthcare AG. NEWS (02.05.2019): "Multi-shot Echo Planar Imaging for accelerated Cartesian MR Fingerprinting: an alternative to conventional spiral MR Fingerprinting" is out for publication in Magnetic Resonance Imaging journal. Read more about it here. NEWS (30.04.2019): Excited to give an invited seminar on "inexact projected gradient methods" for a great audience and field experts at the Department of Mathematical Engineering, Université Catholique de Louvain. NEWS (1.04.2019): Chairing "Machine learning and Inverse problems" symposium at this year's British Applied Mathematics Colloquium (BAMC). NEWS (15.02.2019):"Deep MR Fingerprinting with total-variation and low-rank subspace priors" is accepted by ISMRM 2019 for an oral powerpitch presentation. Read more about it here. NEWS (7.02.2019): Two papers on quantitative MRI accepted by the ISMRM 2019! NEWS (5.02.2019): Matthias Ehrhardt and I are organising two minisymposiums on inverse problems at the British Applied Mathematics Colloquium (BAMC). NEWS (1.02.2019): "Geometry of deep learning for MR fingerprinting", accepted by ICASSP 2019 (oral presentation). Read more about it here. NEWS (5.9.2018): our Rest-Katyusha paper got accepted by NIPS 2018! NEWS (22.8.2018): we will present our deep learning work for MR Fingerprinting in iTWIST 2018 workshop in Marseilles. NEWS (13.8.2018): visiting GE Healthcare Global Research and Technical University (Bioengineering school) in Munich: great atmosphere, loads of MR Fingerprinting data to be acquired!