Institute for Mathematical Innovation

One Day on Compressive Sensing

Advances in theory, algorithms, and applications


University of Bath, 1 June 2017 


Compressive-sensing-imageCompressive sensing is a powerful mathematical theory widely used in Statistics, Computer Science, Engineering and Physics.

Central to this theory is that sparse quantities can be reconstructed using a small number of random measurements.

Recent years have seen an explosion of research activities within this interdisciplinary field, and compressive sensing techniques have now become of key importance in signal processing applications, including medical and astronomical imaging.


Bringing together world-renowned experts and early career researchers, this workshop will:

  • give participants a common understanding of the theory of compressive sensing
  • present recent theoretical and algorithmic developments within the field
  • address key applications

The workshop will also cover interconnected areas including: 

  • sampling paradigms
  • theoretical estimates and algorithms for recovery
  • TV regularisation
  • radio-interferometric astronomical imaging
  • tomographic imaging

Throughout the workshop, there will be ample networking opportunities aimed at fostering collaborations between scientists in the field of compressive sensing. 



Workshop programme 

Registration and coffee
Welcome and initial remarks                                                                       
Dr Silvia Gazzola, Department of Mathematical Sciences, University of Bath
Introduction to Compressive Sensing  
Coffee and discussions
Dr Thomas Blumensath, Faculty of Engineering and the Environment, University of Southampton
Greedy algorithms for Compressed Sensing
Dr Xiaohao Cai, Mullard Space Science Laboratory, University College London
High-Dimensional Uncertainty Estimation with Sparse Priors for Radio Interferometric Imaging
Lunch and discussions
Professor Jared Tanner, Mathematical Institute, University of Oxford
Compressed session with expander graphs: robust-l0 decoding
Dr Clarice Poon, Centre for Mathematical Sciences, University of Cambridge
Breaking the coherence barrier in compressed sensing
Coffee and discussions
Dr Marta Betcke, Department of Computer Science, University College London
Structured guided Total Variation
Dr Yves van Gennip, School of Mathematical Sciences, University of Nottingham
Blind deblurring and graph based segmentation for images
17:00 - 17:30
Concluding remarks & reception


Venue: University of Bath, Claverton Down, Bath, BA2 7AY - Building 4 West, Room 1.1


Workshop organiser

Dr Silvia Gazzola, Department of Mathematical Sciences, University of Bath

For further information about the workshop, contact Institute for Mathematical Innovation at


Workshop supporters

The workshop was supported by an LMS 'Celebrating New Appointments' grant, the Institute for Mathematical Innovation, and the Faculty of Science at the University of Bath.


Workshop presentations