• [PDF] Parameter learning in tomography: Optimal strategy and convergent algorithm
• [PDF] Stratégie bayésienne et échantillonnage stochastique pour la comparaison de modèles. Application en astronomie
• [PDF] Model comparison and parameter learning in inverse problems -- Bayesian strategy and stochastic sampling

• [PDF] Neural network prior and full Bayesian sampling for image deconvolution
• [PDF] Déconvolution en signal-image : approche convexe pénalisée et contrainte
• [PDF] Déconvolution d'images : approche bayésienne autodidacte-myope et sélection de modèle
• [PDF] Déconvolution -- Segmentation jointe
• [PDF] Approche bayésienne hiérarchique pour la découverte de biomarqueur en protéomique
• [PDF] Imagerie ISAR-3D à données incomplètes en mode polarisé pour le contrôle industriel : reconstruction d'image, régularisation, pénalisation, parcimonie

• Name : Jean-François Giovannelli
• Place and date of birth : Béziers, France, in 1966 or 1976 (I do not remember)

• Habilitation à Diriger des Recherches, Signal-Image Processing, Laboratoire des Signaux et Systèmes (L2S), Université Paris-Sud (UPS), Orsay, France, in 2005. Dissertation title "Inversion et régularisation" [PDF]
• Ph.D. Thesis, Signal-Image Processing, Laboratoire des Signaux et Systèmes (L2S), Université Paris-Sud (UPS), Orsay, France, in 1995. Dissertation title "Caractérisation spectrale en temps court. Application à l'échographie Doppler.'' ("Short time spectral characterization. Application to Doppler velocimetry.")
• Graduated from the École Nationale Supérieure de l'Électronique et de ses Applications (ENSEA) in 1990.

• Professor with Université Bordeaux within the UF Sciences de l'ingénieur and IMS Lab (Univ. Bordeaux, CNRS, BINP), Signal and image processing
• Previously : assistant professor (Maître de Conférences), Signal and image processing, Département de Physique at UPS.
• Temporary position (sabbatic): associate researcher
  • October-December 2006: ENST, STA
  • January-March 2006: (previously LIF Unité INSERM 678) Laboratoire d'Imagerie Biomédicale  

• Basics in signal and image modeling and processing
  • Deterministic: Fourier, Laplace and Z-transforms, convolution, 1D and 2D, contionuous-time and discrete time,...
  • Stochastic: second order analysis, correlation, stationarity, power spectral density and also Gaussian fields, Potts field,...
• Bayesian statistics in signal and image: likelihood, Fisher information, prior, cost and risk, MMSE and properties, posterior,... Stochastic sampling, Markov Chain Monte-Carlo (Gibbs, Metropolis-Hastings,...).
• Inverse problems, regularization: quadratic penalties (Wiener, Hunt, Tikhonov), convex penalty (Huber, Total Variation,...), half-quadratic approaches and Legendre-Fenchel transform, augmented Lagrangian algorithm and ADMM, unsupervised problems and hyperparameter estimation, myopic and semi-blind problems, Bayesian approaches, stochastic sampling,... (See Inverse Problem Course section below). 
• And also: 

• Master New (future ex) master in Signal and image processing
• Formation courte, formation continue
• Stratégies bayésiennes en ingénierie : optimalité et échantillonnage stochastique
• Problèmes inverses et imagerie : régularisation et résolution accrue

• Regularization methods for inverse problems in signal and image processing.
• Penalizations and constraints, convex approaches, augmanted Lagrangian algorithm, Alternative Direction Methods of Multilpliers (ADMM)
• Full Bayesian, hierarchical approach, stochastic sampling, MCMC,...
• Model selection and comparison
• Sorry : no-wavelet-ridgelet-curvelet, fuzzyfree approaches, no-PDE methods for image processing,...
• Spectral characterization : spectral analysis, time frequency, frequency tracking, inverse aliasing, Fourier synthesis, deconvolution.
• Deconvolution, unsupervised and myopic (semi-blind) problems.
• Parsimonious models (but not parcimaniac nor porcimoniac) and non-parsimonious ones, depending on their relevance for the problem at hand, LASSO, Group-LASSO
• Application fields: radars (SAR, Doppler,...), medical imaging (Doppler, MRI), astrophysics, proteomics, texture, hyperspectral...

• BHI-PRO: Bayesian Hierarchical Inversion in PROteomics (2011-2013) [LINK].
• BNP-SI : Bayesian non parametric methods for Signal and Image processing (2014-2017) [LINK].

        Slides

• [PDF] Introduction and examples
• [PDF] Linear solutions: least-square and inverse filtering, quadratic penalty and Wiener-Hunt solution,...
• Bayesian interpretation and hyperparameter estimation (slideless... ;-) chalk and blackboard...)
• [PDF] Convex penalty and edge preservation: Huber and half-quadratic approach... 
• [PDF] Positivity and support constraints, Alternative Direction Methods of Multilpliers (ADMM)
• [PDF] Quadratic minimization, system solvers, matrix inversion: a short and partial view...
• [PDF] An example in astronomy: bi-model, smoothness and parsimony, positivity and support, ADMM...
• [PDF] An example in radar imaging: high resolution and sparsity, ADMM...
• [PDF] Concluding remarks and perspectives

        Exercises

• [PDF] Circulant matrices, quadratic functions, Legendre transform, linear constraints, sparsity, denoising,...

        MatlabWork

• [PDF] Linear solutions: quadratic penalty and Wiener-Hunt solution, case of least-square and inverse filtering.
• [PDF] Bayesian standpoint and stochastic sampling for hyperparameter estimation.
• [PDF] Convex penalty and edge preservation: Huber and half-quadratic approach.
• [PDF] Positivity constraints and ADMM.

    Formation Ecole Doctorale  : Inversion et imagerie haute résolution

    En master : Inversion et imagerie

• Problèmes inverses en traitement des signaux et des images
• Problèmes inverses en traitement des signaux et des images (deuxième édition)
• et aussi en Optimisation

    GdR-ISIS : Three meetings and thirty talks links to the slides    

    Workshops :

• High-dimensional Stochastic Simulation and Optimisation in Image Processing, 27-29 August 2014
• New mathematical methods in computationale imaging Heriot-Watt, 29 June 2017

• Problèmes inverses

• [PDF]  Vraisemblance, Fisher, Fisher et Kulback, Posterior, coût et risque, estimation (exemple Gauss, exponentiel,...).

    Travaux pratique sous Matlab

• [PDF] Travaux introductifs: simulation et observation (Gauss et uniforme, couple et corrélation, mélange de deux gaussiennes).
  
• [PDF] Un exemple basique: estimation des paramètres d'une densité Gamma...
• [PDF] Un exemple en thermique: estimation d'un coefficient de diffusivité / convection
• [PDF] Cas du mélange de deux gaussiennes scalaire: identification des paramètres
• [PDF] Identification des paramètres d'un système du second ordre
• [PDF] Analyse de raies

• [PDF]  Variables continues et discrètes, méthode directes et MCMC, Gibbs et Metropolis-Hastings...

• Stratégies bayésiennes en ingénierie

• [PDF] C. Kemajou Mbakam, M. Pereyra, and J.-F. Giovannelli, "Marginal likelihood estimation in semi-blind image deconvolution: A stochastic approximation approach.", submitted SIAM 2023.
• [PDF] A. Yan, L. M. Mugnier, J.-F. Giovannelli, R. Fétick, and C. Petit, "Marginalized blind deconvolution of Adaptive Optics corrected images using MCMC methods", JATIS 2023.
• [PDF] P. Bohra, P. del Aguila Pla, J.-F. Giovannelli and M. Unser, "A Statistical Framework to Investigate the Optimality of Signal-Reconstruction Methods", IEEE Transactions on Signal Processing, vol. 71, pp. 2043-2055, 2023.
• [LINK] J.-M. Lalande, G. Bourmaud, P. Minvielle, and J.-F. Giovannelli, "A kriging-based analysis of cloud liquid water content using CloudSat data", Atmospheric Measurement Techniques, vol. 15, no 15, 2022.
• [PDF] J. Boissy, J.-F. Giovannelli, and P. Minvielle, "An insight into the Gibbs sampler: keep the samples or drop them?", IEEE Signal Processing Letters, 2020.
• [PDF] T. Benoudiba-Campanini, J.-F. Giovannelli, and P. Minvielle, " SPRITE : A New Sparse Approach for 3D High Resolution RCS Imaging", IEEE Transactions on Computational Imaging, vol. 6, 2020.
• [PDF] T. Benoudiba-Campanini, J.-F. Giovannelli, and P. Minvielle, "SPRITE: 3-D SParse Radar Imaging TEchnique", IET Radar, Sonar & Navigation, 2020
• [PDF] C. Vacar and J.-F. Giovannelli, "Unsupervised joint deconvolution and segmentation method for textured images: A Bayesian approach and an advanced sampling algorithm", EURASIP Journal on Advances in Signal Processing, special issue on Advanced Computational Methods for Bayesian Signal Processing, march 2019.
• [LINK] B. Ait-El-Fquiha, J.-F. Giovannelli, N. Paul, A. Girard, I. Hoteit, "Parametric Bayesian estimation of point-like pollution sources of groundwater layers", Signal Processing, 2019.
• [LINK] C. Michelet, Z. Li, W. Yang, S. Incerti, P. Desbarats, J.-F. Giovannelli, P. Barberet, M.-H. Delville, N. Gordillo, G. Devès, and H. Seznec, "A Geant4 simulation for three-dimensional proton imaging of microscopic samples", Physica Medica, vol. 65, pp. 172-180, Septembre 2019.
• [LINK] V. Picaud, J.-F. Giovannelli, C. Truntzer, J.-P. Charrier, A. Giremus, P. Grangeat, C. Mercier, "Linear MALDI-ToF simultaneous spectrum deconvolution and baseline removal", BMC Bioinformatics, vol. 19, no 123, 2018.
• A. Klich,  C. Mercier, L. Gerfault, P. Grangeat, C. Beaulieu, E. Degout-Charmette, T. Fortin, P. Mahé, J.-F. Giovannelli, J.-P. Charrier, A. Giremus, D. Maucort-Boulch and P. Roy, "Variance component analysis to assess protein quantification in biomarker validation: Application to SRM mass spectrometry", BMC Bioinformatics, January 2018.
• [PDF] N. Dridi, A. Giremus, J.-F. Giovannelli, C. Truntzer, M. Hadzagic, J.-P. Charrier, L. Gerfault, P. Ducoroy, B. Lacroix, P. Grangeat and P. Roy, "Bayesian inference for biomarker discovery in proteomics: an analytic solution", EURASIP Journal on Bioinformatics and Systems Biology, vol. 9, December 2017.
• C. Mercier, A. Klich,  C. Truntzer, V. Picaud, J.-F. Giovannelli, P. Ducoroy, P. Grangeat, D. Maucort-Boulch and P. Roy, "Variance component analysis to assess protein quantification in biomarker discovery: Application to MALDI-TOF mass spectrometry", Biometrical Journal, December 2017.
• [PDF] P. Minvielle, P. Massaloux, and J.-F. Giovannelli, "Indoor 3D Radar Imaging for Low-RCS", IEEE Transactions on Aerospace and Electronic System, vol. 53, no. 2, pp. 995-1008, February 2017.
• C. Michelet, P. Barberet, P. Desbarats, J.-F. Giovannelli, C. Schou, I. Chebil, M.-H. Delville, N. Gordillo, D. G. Beasley, G. Devès, P. Moretto and H. Seznec, "An implementation of the NiftyRec medical imaging library for PIXE-tomography reconstruction", Nuclear Instruments and Methods in Physics Research, Section B: Beam Interactions with Materials and Atoms, vol. 404, pp. 131-139, August 2017.
• [PDF] O. Féron, F. Orieux, and J.-F. Giovannelli, "Gradient scan Gibbs sampler: an efficient algorithm for high-dimensional Gaussian distributions", IEEE Journal of Selected Topics in Signal Processing, vol. 10, no 2, pp. 146-159, 2016.
• [PDF] C. Vacar, J.-F. Giovannelli, Y. Berthoumieu, "Bayesian texture classification from indirect observation unsing fast sampling", IEEE Trans. Signal Processing, vol. 64, no 1, pp. 343-352, 2016.
• [PDF] P. Szacherski, J.-F. Giovannelli, L. Gerfault, P. Mahé, J.-P. Charrier, A. Giremus, B. Lacroix and P. Grangeat, "Classification of proteomic MS data as Bayesian solution of an inverse problem", IEEE Access, vol. 2, pp. 1248-1262, September 2014.
• [PDF] C. Vacar, J.-F. Giovannelli, Y. Berthoumieu, "Bayesian texture and instrument parameter estimation from blurred and noisy images unsing MCMC", Signal Processing Letters, vol. 21, no 6, pp. 707–711, 2014.
• [PDF] A. Hazart, J.-F. Giovannelli, S. Dubost, and L. Chatellier, "Inverse transport for point-like source estimation with a Bayesian parametric method coupled with MCMC algorithm", Signal Processing, vol. 96, pp 346-361, 2014.
• [PDF] F. Orieux, J.-F. Giovannelli, T. Rodet, and A. Abergel, "Estimation of hyperparameters and instrument parameters in regularized inversion. Illustration for SPIRE/Herschel map making.", Astronomy and astrophysics, vol. 549, January 2013.
• [PDF] F. Orieux, O. Féron and J.-F. Giovannelli, "Sampling high-dimensional Gaussian distributions for general linear inverse problems", Signal Processing Letters, vol. 19, no. 5, pp. 251-254, May 2012. (See Python Notebook below).
• [PDF] F. Orieux, J.-F. Giovannelli, T. Rodet, H. Ayasso and A. Abergel, "Super-resolution in map-making based on a physical instrument model and regularized inversion. Application to SPIRE/Herschel", Astronomy and astrophysics, vol. 539, March 2012.
• [PDF] F. Orieux, J.-F. Giovannelli and T. Rodet, "Bayesian estimation of regularization and PSF parameters for Wiener-Hunt deconvolution", JOSA-A, vol. 7, no. 27, pp. 1593-1607, July 2010.  (See Matlab Code below).
• [PDF] E. Thiébaut and J.-F. Giovannelli, "Image Reconstruction in Optical Interferometry", IEEE Signal Processing Magazine, vol. 27, no. 1, pp. 97-109, January 2010. 
• [PDF] T. Rodet, F. Orieux, J.-F. Giovannelli, and A. Abergel, "Data Inversion for Over-Resolved Spectral Imaging in Astronomy", IEEE Journal of Selected Topics in Signal Processing, vol. 2, no. 5, pp. 802-811, October 2008. 
• [PDF] J.-F. Giovannelli, "Unsupervised Bayesian convex deconvolution based on a field with an explicit partition function", IEEE Trans. Image Processing, vol. 17, no. 1, pp. 16-23, January 2008. 
• [PDF] G. Rochefort, F. Champagnat, G. Le Besnerais and J.-F. Giovannelli, "An Improved Observation Model for Super-Resolution under Affine Motion", IEEE Trans. Image Processing, vol. 15, no. 11, pp. 3325-3337, November, 2006.
• [PDF] R. Boubertakh, J.-F. Giovannelli, A. Herment and A. De Cesare, "Non-quadratic convex regularized reconstruction of MR images from spiral acquisitions", Signal Processing, vol. 86, pp. 2479-2494, 2006.
• [PDF] J.-F. Giovannelli and A. Coulais, "Positive deconvolution for superimposed extended sources and  point sources", Astronomy and astrophysics, vol. 439, pp. 401-412, 2005. (See Matlab Code below).
• [PDF] V. Samson, F. Champagnat and J.-F. Giovannelli, "Detection of Point Objects with Random Subpixel Location and Unknown Amplitude", Applied optics, Special Issue on Image processing for EO sensors, vol. 43, no.2, pp. 257-263, January 2004.
• [PDF] J.-F. Giovannelli , J. Idier, R. Boubertakh, and A. Herment, "Unsupervised Frequency Tracking beyond the Nyquist Limit using Markov Chains", IEEE Trans. Signal Processing, vol. 50, no. 12, pp. 2905-2914, December, 2002.
• C. Berthomier, A. Herment, J.-F. Giovannelli, G. Guidi, L. Pourcelot, and B.Diebold, "Multigate Doppler Signal Analysis using 3-D Regularized Long AR Modeling", Ultrasound in Medicine and Biology, vol. 27, no. 11, pp. 1515-1523, 2001.
• [PDF] A. Mohammad-Djafari, J.-F. Giovannelli, G. Demoment, and J. Idier, "Regularization, Maximum Entropy and Probabilistic Methods in Mass Spectrometry Data Processing Problems", Int. Journal of Mass Spectrometry, vol. 215, no. 1-3, pp. 175-193, April 2002.
• [PDF] J.-F. Giovannelli, J. Idier, G. Desodt, and D. Muller, "Regularized adaptive long autoregressive spectral analysis", IEEE Trans. Geosci. Remote Sensing, vol. 39, no. 10, pp. 2194-2202, October 2001.
• [PDF] P. Ciuciu, J. Idier, and J.-F. Giovannelli, "Regularized estimation of mixed spectra using a circular Gibbs-Markov model", IEEE Trans. Signal Processing, vol. 49, no. 10, pp. 2201-2213, October 2001.
• [PDF] J.-F. Giovannelli and J. Idier, "Bayesian interpretation of periodograms", IEEE Trans. Signal Processing, vol. 49, no. 7, pp. 1988-1996, July 2001.
• [PDF] J. Idier and J.-F. Giovannelli, "Structural stability of least squares prediction methods", IEEE Trans. Signal Processing, vol. 46, no. 11, pp. 3109-3111, November 1998.
• [PDF] A. Herment, J.-F. Giovannelli, G. Demoment, B. Diebold, and A. Delouche, "Improved characterization of non stationary flows using a regularized spectral analysis of ultrasound Doppler signals", Journal de Physique III, vol. 7, no. 10, pp. 2079-2102, October 1997.
• [PDF] J.-F. Giovannelli, G. Demoment, and A. Herment, "A Bayesian method for long AR spectral estimation: a comparative study", IEEE Trans. Ultrasonics Ferroelectrics Frequency Control, vol. 43, no. 2, pp. 220-233, March 1996.
• A. Herment and J.-F. Giovannelli, "An adaptive approach to computing the spectrum and mean frequency of Doppler signals", Ultrasonic Imaging, vol. 27, pp. 1-26, 1995.

Book coordination (collective contribution)

• J.-F. Giovannelli, and J. Idier, "Méthodes d'inversion appliquées au traitement du signal et de l'image", Traité IC2, Série traitement du signal et de l'image, Hermès, November 2013
• J.-F. Giovannelli, and J. Idier, "Regularization and Bayesian Methods for Inverse Problems in Signal and Image Processing", ISTE Ltd and John Wiley & Sons Inc, February 2015.

Book chapters

     ... and a Chinese version now available here !!

• G. Le Besnerais, J.-F. Giovannelli, and G. Demoment, "Inverse Filtering and Other Linear Methods", ch. 4, pp.80-116 in Bayesian Approach to Inverse Problems, ISTE Ltd and John Wiley & Sons Inc, 2008, J. Idier, editor.
• J.-F. Giovannelli , and A. Herment, "Spectral Characterization in Ultrasonic Doppler Velocimetry", ch. 11, pp.271-295 in Bayesian Approach to Inverse Problems, ISTE Ltd and John Wiley & Sons Inc, 2008, J. Idier, editor.
• G. Le Besnerais, J.-F. Giovannelli, and G. Demoment, "Filtrage inverse et méthodes linéaires en déconvolution", ch. 4, pp.81-114 in Approche bayésienne pour les problèmes inverses, Traité IC2, Série traitement du signal et de l'image, Hermès, 2001, J. Idier, editor.
• J.-F. Giovannelli , and A. Herment, "Caractérisation spectrale en vélocimétrie Doppler ultrasonore", ch. 11, pp.271-295 in Approche bayésienne pour les problèmes inverses , Traité IC2, Série traitement du signal et de l'image, Hermès, 2001, J. Idier, editor.
• G. Demoment, J. Idier, J.-F. Giovannelli, A. Mohammad-Djafari, "Problèmes inverses en traitement du signal et de l'image", Techniques de l'Ingénieur, Traité Télécoms , vol. TE 5235, pp.1-25, 2001.

Habilitation

• [PDF] J.-F. Giovannelli, "Inversion et régularisation", Habilitation à Diriger des Recherches, Université Paris Sud, 12 décembre 2005.

• G. Guillot et J.-F. Giovannelli, "UTE-IR4M: un logiciel pour la reconstruction d'images par IRM", déclaration d'invention 2015, Logibox APP N° 122380, IDDN.FR.001.080011.000.S.P.2019.000.31230, 12 février 2019.
  
• P. Szacherski, P. Grangeat et J.-F. Giovannelli, "Procédé et dispositif d'estimation de paramètres biologiques ou chimiques dans un échantillon, procédé d'aide au diagnostic correspondantdé", avril 2011, Brevet français étendu aux Etats-Unis (d'Amérique), N° 11-53008, CEA/CNRS
• G. Strubel, J.-F. Giovannelli, et P. Grangeat, "Procédé d'estimation de concentrations de molécules dans un relevé d'échantillon et appareillage", août 2007, Brevet français étendu aux Etats-unis (d'Amérique), N° 07-57-131, CEA/CNRS
• S. Brette, H. Carfantan, J.-F. Giovannelli, T. Martin, J.-F. Bercher, C. Heinrich, J. Idier et C. Soussen, "Gradient à Pas Adaptatif avec Corrections, une mise en oeuvre Matlab : GPAC.m", déclaration d'invention N° DI-0258-01, Logibox APP N° 21961, IDDN.FR.001.070033.000.S.P.2006.000.10800,  16 février 2006. [PDF DocCourte] [PDF DocLongue]

• Matlab Code (IDL Code coming soon or never) for positive deconvolution of superimposed extended sources and  point sources (see Astronomy and astrophysics paper above) [DownLoad]
• Matlab Code for regularization and instrument parameters in deconvolution (see JOSA paper above) [LINK]
• Python Code for Sampling high-dimensional Gaussian distributions (see Signal Processing Letters paper above) [LINK]

• Lisa Garcia, 2023-, Apprentissage machine pour la dynamique rapide: dépouillement de données expérimentales, calibration de paramètres et comparaison de modèles physiques, co-advisor : Gaël Poette, collaboration with CEA-CESTA.
• Pierre Minier, 2023-, Déconvolution pour l’imagerie à haute résolution. Application à l'imagerie en astronomie, co-advisor : François Orieux, collaboration with Paris-Saclay, in addition to PEPR-Origins and RRI-Origins.
• Liam Moroy, 2022-, Réseaux de neurones et approche bayésienne pour l'imagerie de turbulences à haute résolution, collaboration with ONERA-DTIS, co-advisor : Frédéric Champagnat and Guillaume Bourmaud.
• Charlesquin Kemajou, 2021-, Bayesian and machine learning methods for blind and semi-blind inverse problems in computational imaging: Applications to hyperspectral image super-resolution and radio-astronomy, co-advisor : Marcelo Pereyra
• Alix Yan, [PDF], [Video], 2020-2023, Reconstruction d'images multi-temporelles à haute résolution angulaire dans le visible. Application à l'observation astronomique et l'observation de satellites, collaboration with ONERA-DOTA, co-advisor : Laurent Mugnier
• Julien Boissy, [PDF], 2018-2022, Simulation sous incertitudes pour l'électromagnétisme, co-advisor : Pierre Minvielle, collaboration with CEA-CESTA
• Benjam Harroué, [PDF], 2016-2020, Model selection in inverse problems, co-advisor : Marcelo Pereyra
• Thomas Benoudiba, [PDF], 2015-2018, Imagerie ISAR-3D à données incomplètes en mode polarisé pour le contrôle industriel, co-advisor : Pierre Minvielle, collaboration with CEA-CESTA.
• Andrei Barbos, [PDF], 2014-2018, Efficient High-Dimension Gaussian Sampling based on Matrix Splitting. Application to Bayesian Inversion, co-advisor : François Caron, Department of Statistics, University College Oxford.
• Jessica Sodjo, [PDF], 2014-2018, Non parametric Bayesian model for joint segmentation, main-advisor : Audrey Giremus, others François Caron and Nicolas Dobigeon.
• Cornelia Vacar, [PDF], 2010-2014, Bayesian approach for texture deconvolution-segmentation. Unsupervised and myopic aspects, co-advisor : Yannick Berthoumieu.
• Pascal Szacherski, [LINK], 2010-1012, Molecular profile reconstruction for biomarker discovery, collaboration with LETI (CEA-DRT), co-advisor : Pierre Grangeat.
• François Orieux, [LINK], 2006-2009, Inversion bayésienne : aspects non-supervisés et sur-résolus en milieu incertain et application aux données du satellite Herschel, collaboration with IAS, co-advisor : Thomas Rodet und Alain Abergel (IAS).
• Grégory Strubel, [LINK], 2005-2008, Profile reconstruction for analysis microsystems applied to biology and health care, collaboration with LETI (CEA-DRT), co-advisor : Pierre Grangeat.
• Aurélien Hazart, 2004-2007, Identification of sources of pollution, collaboration with EdF/DER, co-advisor : Laurence Chatellier and Stephanie Dubost.
• Gilles Rochefort, 2001-2005, High resolution imaging from video sequences, collaboration with ONERA-DTIM , co-advisor : Frédéric Champagnat and Guy Lebesnerais.
• Vincent Samson, 1999-2002, Detection of punctual moving objects in image sequences, collaboration with ONERA-DTIM, co-advisor : Frédéric Champagnat.
• Redha Boubertakh, 1998-2002, Fourier synthesis and application to Magnetic Resonance Imaging, collaboration with Unité IMQ, INSERM U494 co-advisor Alain Herment.
• Philippe Ciuciu, [LINK], 1996-2000, Markovian high resolution spectral analysis and application to meteorological radars, collaboration with Société Thomson-CSF-AIRSYS (Daniel Muller and Guy Desodt), main-advisor : Jérome Idier, Ircyn.

• GdR ISIS et GRETSI and EURASIP

• LaBRI et CENBG
• LSS
• Laboratoire d'imagerie Fonctionnelle (LIF), Unité INSERM 678
• Laboratoire d'Astrophysique de Bordeaux et Institut d'Astrophysique Spatiale
• EdF
• ONERA, ONERA-DTIM, ONERA-DOTA
• CEA-CESTA, LETI (CEA-DRT) et LIST(CEA-DRT)
• CLIPP, LBS, bioMérieux

• Marc Allain, Yoann Altmann, Jean-François Bercher, Hervé Carfantan, Philippe Ciuciu, Olivier Feron, Yves Goussard, Christian Heinrich, Mahieddine Ichir, Jérôme Idier, Caroline Kulcsar, Ali Mohammad-Djafari, Laurent Mugnier, Pierre Minvielle, François Orieux, Marcelo Pereyra, Thomas Rodet, Hichem Snoussi, Charles Soussen, Eric Thiebaut

Une maxime --- Rien ne résiste au travail, rien. Georges Duclos, architecte.

Une tentative --- Depuis pas mal de siècles déjà l'humanité cherche à comprendre... Aujourd'hui, elle est sur le point de transférer cette tâche à la machine, sans trop la comprendre.

Autre genre d'activité --- Une réclame pour divers racontars : Les étoiles polaires

Des magiciens --- Ils ont fait de moi un sportif : CAPAS ;-)

Un bouquin --- Quelque chose que j'aurais aimé écrire : Olivier Courcelle, Le théorème de Travolta. L'histoire de trois jeunes ratés du théorème, assez sérieusement névrosés... Sur les travers de nos communautés scientifiques...

Une BD --- Crayon noir --- Samuel Paty. Histoire d'un prof. --- Valérie Igounet et Guy Le Besnerais.