Ming Jiang

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Research Interests

I'm working on the hyperspectral interferometric signal reconstruction. One of the most promising methods is to utilize the concept "Compressed Sensing" to recover a sparse signal, not only in two spatial dimensions but also in time or wavelength dimension.

My research interests mainly include:

Sparse signal processing

• Inverse problem

• Signal/Image reconstruction and restoration

• Sparse representation

• Compressed sensing and its application on radio astronomy.

• Blind Source Separation

• Convex and non-convex optimization

• Dictionary learning

Radio/hyperspectral data

• Radio interferometric imaging

Education

I received a Bachelor's Degree in Electrical and Electronic Engineering from Xidian University in 2011.

From 2010 to 2014, due to the program "3+3" between China and France, I studied in Télécom Bretagne and obtained a Master of Engineering degree with a major in Information Processing Systems. During 2013 - 2014, I obtained a double degree: Master of Research on Image, which was awarded by Télécom Bretagne, Rennes 1 and Supélec, according to the academic program "SISEA".

During my studies, I had an opportunity to participate in "Programme First" of the edition 2012 organized by Fondation Télécom. In addition, I worked as an intern in Alcatel-Lucent France and LaTIM - INSERM U1101.

Publications

Refereed Articles:

• M.Jiang, J.Bobin, J.-L.Starck, Joint Multichannel Deconvolution and Blind Source Separation, SIAM J. Imaging Sci. 10-4 (2017), pp. 1997-2021, doi: 10.1137/16M1103713.

Conference Proceedings:

• M.Jiang, J.Girard, J-L.Starck, S.Corbel, C.Tasse, Compressed Sensing and Radio Interferometry, EUSIPCO 2015, pp.1646 - 1650, doi : 10.1109/EUSIPCO.2015.7362663 (refereed)
• M.Jiang, J.Girard, J-L.Starck, S.Corbel, C.Tasse, Interferometric Radio Transient Reconstruction In Compressed Sensing Framework, SF2A-2015, pp.231-236, 2015

Abstracts:

• M.Jiang, J.Bobin, J.-L.Starck, Joint Multichannel Deconvolution and Blind Source Separation, SPARSE 2017
• M.Jiang, J.Bobin, J.-L.Starck, Joint Deconvolution and Blind Source Separation of Hyperspectral Data Using Sparsity, 2016 SIAM Conference on Imaging Science (IS16), Albuquerque, New Mexico, USA

Communications

Contribution to conferences:

• May 23 - 26, 2016 SIAM Conference on Imaging Science, Albuquerque, New Mexico, USA (talk)
• January 10 - 16, 2016 Winter School: Advances in Mathematics of Signal Processing, Bonn, Germany (poster)
• August 31 - September 4, 2015 EUSIPCO 2015, Nice, France (talk)
• June 2 - 5, 2015 SF2A-2015, Toulouse, France (talk)
• November 13 - 14, 2014 Rencontres d'Astrostatistique 2014, Grenoble, France (talk)

Talks:

• November 2016 PHySIS 5th technical meeting, CEA Saclay, France
• July 2016 COSMIC kick-off meeting, Neurospin, CEA Saclay, France
• August 2015 Department of Mathematics, HIT (Harbin Institute of Technology), China

Softwares

Joint Deconvolution and Blind Source Separation (DBSS) method: DecGMCA 

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