Research output per year
Research output per year
Accepting PhD Students
PhD projects
Compressed sensing and sparse representations in signal processing and machine learning
Mike Davies holds the Jeffrey Collins Chair in Signal and Image Processing at the University of Edinburgh where he leads the Edinburgh Compressed Sensing Research Group. He was Head of the Institute for Digital Communications (IDCom) in the School of Engineering 2013-16 and Director of the Joint Research Institute in Signal and Image Processing (JRI-SIP) a the collaborative research venture between the University of Edinburgh and Heriot-Watt University as part of the Edinburgh Research Partnership.
He received an M.A. in engineering from Cambridge University in 1989 where he was awarded a Foundation Scholarship (1987), and a Ph.D. degree in nonlinear dynamics and signal processing from University College London (UCL) in 1993. In 1993 he was awarded a Royal Society University Research Fellowship. He currently manages a £7M portfolio of research grants from a variety of sources including: EPSRC, Dstl, industry, EU and the ERC, and leads the University Defence Research Collaboration (UDRC), a UK programme of signal processing research in defence in collaboration with the UK Defence Science and Technology Laboratory (Dstl).
Fellow of the Royal Society of Edinburgh (2018)
Fellow of the Royal Academy of Engineering (2017)
Royal Society Wolfson Research Merit Award (2016)
Fellow of the European Association of Signal Processing (2016)
Fellow of the IEEE (2015)
Texas Instruments Distinguished Visiting Professor, Rice University (2012)
My work focusses on the fields of sparse representations and compressed sensing, and their application to various signal processing, imaging and machine learning problems. During the past decade I have made significant contributions to the key areas of fundamental CS theory, new signal models, including dictionary learning techniques, the development and analysis of new reconstruction algorithms, This work includes: the proposal and analysis of the highly popular Iterative Hard Thresholding family of algorithms for sparse reconstruction; the development of new reconstruction theory for structured sparse signal models; the introduction and analysis for a new model (co-sparsity) for redundant analysis representations; and the characterization of types of statistical distribution that admit accurate low dimensional approximations.
I have applied these ideas to a number of applications including: chemical identification in Raman spectroscopy, dynamic MRI and 3D brain imaging, a new compressed sensing framework for quantitative MRI, electronic surveillance and Synthetic Aperture Radar.
Current Projects
ERC Advanced Grant: C-SENSE, "Exploiting Low Dimensional Models in Sensing, Computation and Processing"
The aim of this project is to develop the next generation of compressive and computational sensing and processing techniques.
UDRC: University Defence Research Collaboration in Signal Processing
An academia led partnership between the defence industry, academia and the government sector. The UDRC develops research in signal processing with application to the defence industry.
Recent Past Projects
CQ-MRI: EPSRC funded award in Compressed Quantitative MRI
The proposed research will provide the first proof-of-principle for a new family of Compressed Quantitative Magnetic Resonance Imaging (CQ-MRI), able to rapidly acquire a multitude of physical parameter maps for the imaged tissue from a single scan.
CIRI: EPSRC funded award in Compressed Imaging in Radio Interferometry
The CIRI project aims to bring new advances for interferometric imaging for next-generation radio telescopes, together with theoretical and algorithmic evolutions in generic compressive imaging.
MacSeNet: Machine Sensing Training Network
Professional Activities
2013 – date Member of IEEE Sig. Proc. Theory and Methods technical committee
Doctor of Philosophy (PhD), Noise Reduction in Nonlinear Time Series Analysis, University College London
Award Date: 1 Dec 1993
Bachelor of Arts, University of Cambridge
Award Date: 1 Jan 1989
Research output: Contribution to journal › Article › peer-review
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Research output: Contribution to journal › Article › peer-review
Research output: Contribution to journal › Article › peer-review
Tachella, Julián (Recipient), Sheehan, Mikey (Recipient) & Davies, Michael (Recipient), 27 May 2022
Prize: Prize (including medals and awards)
Davies, M., Hopgood, J., Hospedales, T., Mulgrew, B., Thompson, J., Tsaftaris, S. & Yaghoobi Vaighan, M.
1/07/18 → 31/03/24
Project: Research
Hopgood, J., Davies, M. & Mulgrew, B.
UK central government bodies/local authorities, health and hospital authorities
6/10/21 → 6/07/22
Project: Research
UK industry, commerce and public corporations
1/08/19 → 30/06/20
Project: Research
Hopgood, J., Davies, M. & Yaghoobi Vaighan, M.
UK industry, commerce and public corporations
1/09/18 → 31/10/19
Project: Research
Bano, W. (Creator), Golbabaee, M. (Creator), Benjamin, A. (Creator), Marshall, I. (Creator) & Davies, M. (Creator), Edinburgh DataShare, 31 Aug 2018
DOI: 10.7488/ds/2428, https://www.research.ed.ac.uk/portal/en/publications/improved-accuracy-of-accelerated-3d-t2-mapping-through-coherent-parallel-maximum-likelihood-estimation(ce799d8e-6c37-4bb6-be2b-abef5897d5f4).html
Dataset
Mair, G. (Creator), Marshall, I. (Creator), Davies, M. (Creator), Benjamin, A. (Creator) & Bano, W. (Creator), Edinburgh DataShare, 22 Jan 2019
DOI: 10.7488/ds/2486
Dataset
3/08/16
2 items of Media coverage
Press/Media: Research
1/04/14
3 items of Media coverage
Press/Media: Research