"Séminaire d'Automatique du plateau de Saclay" of iCODE

Seminar on October 25, 2019, 10:00 AM at CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Antoine Girard & Sajad Naderi


10:00-11:00 Antoine Girard (L2S, Gif-Sur-Yvette, France)

Title: A Symbolic Control Approach to the Programming of Cyber-Physical Systems

Abstract: Autonomous vehicles, intelligent buildings or robots promise to transform the everyday life of our society in all its dimensions (transport, housing, industry, health, assistance to the elderly ...). These systems are examples of cyber-physical systems (CPS) resulting from the integration of computer components and physical processes. The development of these systems is often complex (due to cyber-physical interactions) and with critical safety requirements.
In this talk, I will present the first steps towards developing a framework for CPS programming that will enable fast and safe development of their functionality through a high-level programming language. The originality of the approach is to consider that programs are not intended to be executed on the digital platform made up of computer components, but on the cyber-physical platform, which additionally includes the physical part of the system. Thus, high-level programs do not specify the behavior of the computer components but directly that of the cyber-physical system. Then, an automatic synthesis tool uses a model of the physical process to generate low-level control algorithms that enforce the specified behavior.
I will introduce a high-level language for CPS directly inspired by the formalism of hybrid automata. Following the paradigm of 'correct by construction synthesis', low-level control algorithms are synthesized by symbolic control techniques. The key concept of symbolic control is that of the symbolic model, which is a dynamic finite state system, obtained by abstracting physical trajectories on a finite set of symbols. When symbolic and physical dynamics are formally linked by a behavioral relation (e.g., simulation or bisimulation), controllers synthesized for the symbolic model using discrete synthesis techniques can be refined to controllers certified for the physical system. I will provide illustrating examples from the domain of autonomous vehicles.

Biography: Antoine Girard is a senior researcher at CNRS and a member of the Laboratory of Signals and Systems. He received the Ph.D. degree in applied mathematics from Grenoble Institute of Technology, in 2004. From 2004 to 2006, he held postdoctoral positions at University of Pennsylvania and Université Grenoble-Alpes. From 2006 to 2015, he was an Assistant/Associate Professor at the Université Grenoble-Alpes. His main research interests deal with analysis and control of hybrid systems with an emphasis on computational approaches, formal methods and applications to cyber-physical systems. Antoine Girard received the George S. Axelby Outstanding Paper Award from the IEEE Control Systems Society in 2009. In 2014, he was awarded CNRS Bronze Medal. In 2015, he was appointed as a junior member of the Institut Universitaire de France (IUF). In 2016, he was awarded an ERC Consolidator Grant. In 2018, he received the first Test of Time Award from the International Conference on Hybrid Systems: Computation and Control and the European Control Award.

11:00-12:00 Sajad Naderi (Eindhoven University of Technology, The Netherlands)

Title: Model order reduction for linear time delay systems based on energy functionals

Abstract: In this talk, I first present a model order reduction approach for asymptotically stable linear time systems with point-wise delays. This approach, which can be regarded as an extension of existing balanced model order reduction techniques for linear delay-free systems, is based on energy functionals that characterize observability and controllability properties of time delay system. This type of approach provides an a priori bound on the reduction error. Moreover, the resulting reduced model is an asymptotically stable time delay system with the same delay-structure as the original model. In the second part of the presentation, I introduce an extended model order reduction technique for time delay systems. This extension is beneficial when the preservation of physical interconnection structures or uncertainties is desired.

Biography: Sajad Naderi received his MSc in control systems from the school of electrical and computer engineering at the University of Tehran, Iran. For his MSc thesis, he worked on the design and implementation of nonlinear adaptive controllers for the speed control of PMSM drives. He is currently pursuing a PhD degree within the dynamics and control group of the mechanical engineering department at Eindhoven University of Technology, The Netherlands. His PhD research focuses on model order reduction of infinite-dimensional systems, with application to managed pressure drilling automation. In the scope of this industrial project, he has spent 1.5 years of his PhD at the Norwegian company Kelda Drilling Controls in Porsgrunn, Norway.

Séminaire Scube CentraleSupélec

Seminar on October 18, 2019, 11:00 AM at CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Diarra FALL


Title: Test d'hypothèses bayésien non paramétrique et application à la modélisation de la zone du langage

 

Abstract: Dans cet exposé je parlerai de modèles bayésiens non paramétriques et de tests d'hypothèses, avec pour exemple d'application, un travail en cours avec le centre hospitalier régional d'Orléans portant sur l'estimation de la zone contrôlant le langage chez des patients ayant eu un AVC.

Biographies: I joined the University of Amiens (France) where I was post-graduated in theoretical Mathematics. Afterward, I received a Master research degree in Data processing from the UVSQ, UPMC & Telecom Sud Paris. I obtained my Ph.D. degree in Image processing from the University Paris Sud. From 2007 to 2011, I did my doctoral research in the Laboratory of Modeling Simulation and Systems at CEA (French Atomic Energy Commission), and in the Laboratory of Signals and Systems (Supélec), in collaboration with Frédéric Joliot Hospital Service. In 2008-2010, I was a teaching assistant in Statistics and Numerical Analysis at ENSIIE Evry. From 2011 to 2013, I was an assistant professor of Mathematics at the University Paris Descartes. Since September 2013, I am an associate professor of Mathematics at the University of Orleans.

Séminaire d'Automatique du plateau de Saclay

Seminar on October 17, 2019, 10:00 AM at CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Islam Boussaada & Ludovic Sacchelli


10:00-11:00 Islam Boussaada (Inria Saclay, Equipe DISCO & L2S, Gif-Sur-Yvette)

Title: Coalescence and Splitting Mechanisms of Spectral Values and their Effect on Stability: Towards a New Framework for Reduced Complexity Pole-placement Design for Time-Delay Systems

Abstract: For linear delay-differential equations, a question of ongoing interest is to determine conditions on the equation parameters that guarantee exponential stability and stabilization of solutions. This talk starts by a review of an old design method for time-delay systems called finite pole-placement. Its advantages and limitations shall be stressed. Next, some recent results showing a link between the stable manifold and the manifold corresponding to a given multiplicity of a spectral value shall be presented, hence enabling a spectral abscissa assignment. After a motivation of the tracking of multiple spectral values for analysis/control perspectives, some existing links between Birkhoff’s interpolation problem and a result due to Pólya and Szegö on the number of quasipolynomial's roots in a horizontal strip shall be revisited. Later, hints of an analytic proof of the dominancy of the quasipolynomial's root will be presented, setting up a reduced-complexity delayed stabilizing design. Sensitivity of the control design with respect to the parameters' variation will be discussed. To overcome the sensitivity of multiple roots, an extension of the approach to real distinct pole assignment shall be presented. Finally, various reduced order examples will illustrate the applicative perspectives of the proposed control approach.

Biography: Islam Boussaada received his Master in Mathematics from University Tunis II, and an M.Sc. degree in Pure Mathematics from University Paris 7 in 2004. In December 2008, he defended his Ph.D. degree in Mathematics from University of Rouen Normandy. In June 2016, he received his HDR degree (French Habilitation) in Physics from University Paris Saclay-University Paris Sud. In 2010, IB was appointed for two years as a post-doctoral fellow in the control of time-delay systems at L2S, Supelec-CNRS-University Paris Sud. Since 2012, he has been an associate professor at IPSA and an associate researcher at MODESTY Team of L2S. Since September 2017, IB is appointed permanent researcher at DISCO Team and full professor at IPSA where he headed the Aeronautical and Aerospace Systems department from September 2017 till May 2019.
Since September 2018 untill August 2020, IB is a researcher in temporary secondment at Inria Saclay-DISCO Team. His research interests belong to the qualitative theory of dynamical systems and its application in control problems. It includes stability analysis and stabilization of linear/nonlinear dynamical systems, analysis of parametric systems, analysis of delay induced dynamics, nonhyperbolic dynamics, analysis of algebraic dierential systems, control of active vibrations, dynamics of biochemical networks. IB is co-author of a monograph and co-editor of a contributed book, both published in Springer series, as well as co-author of more than 60 peer-reviewed publications. He co-organized the 4th GDRI DelSys's Workshop on Observing and Controlling Complex Dynamical Systems (November 2015), as well as the 1st GDRI Spa-Disco's workshop on Delays and Constraints in Distributed Parameters Systems (November 2017), both funded by CNRS and held at CentraleSupelec (Gif sur Yvette). At the occasion of the 20th World Congress of the International Federation of Automatic Control (IFAC) (Toulouse, July 2017), IB co-organized an invited session "Frequency domain Techniques for Time-delay Systems". At the occasion of the 13th-15th IFAC Workshop on Time-delay Systems (Istanbul 2016, Budapest 2018, Sinaia 2019), IB co-organized thematic sessions on Spectral Methods for Rightmost Roots Characterization in LTI Time-delay Systems. Since September 2018, IB is co-leading the national research group GT OSYDI of the CNRS/GDR MACS and is a deputy director of the IRS iCODE Institute of the University Paris Saclay.

11:00-12:00 Ludovic Sacchelli (Lehigh University, Pennsylvania, USA)

Title: Stabilization of non-uniformly observable system

Abstract: A common strategy in dynamic output feedback stabilization is to apply a state feedback to an observer in order to stabilize the coupled state-observer system. It is well known that global stabilizability, paired with uniform observability, implies semi-global stabilisability by dynamic output feedback. However in many generic cases, the system is not uniformly observable, and usual strategies for semi-global stabilization break down. New approaches need to be explored to resolve this issue. We will present case studies to give an outlook for the challenges raised by this problem and highlight a promising answer based on the idea of unitary embeddings of control systems.

Biography: Ludovic Sacchelli is a visiting assistant professor in the Mathematics Department of Lehigh University, in Bethlehem, Pennsylvania. He graduated from Ecole Normale Supérieure de Cachan and received his master's degree in analysis of PDEs from Paris-Sud University in 2015. He obtained a Ph.D. in applied mathematics from Ecole Polytechnique in 2018 on the topic of sub-Riemannian geometry. Ludovic spent the following year as a postdoc in the Electrical Engineering Department of University of Toulon (LIS Lab) before departing for his current position. His research interests lie in sub-Riemannian geometry, control theory and observability.

Control of automated vehicles and their influence on traffic

Seminar on October 03, 2019, 2:00 PM at CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Karl H. Johansson


Abstract: Automated and connected road vehicles enable large-scale control and optimisation of the transport system with the potential to radically improve fuel efficiency, decrease the environmental footprint, and enhance safety. In this talk we will focus on automated heavy-duty vehicle platooning, which is currently being implemented and evaluated by several truck manufacturers world-wide. We will discuss how to deploy feedback control of individual platoons utilising the cellular communication infrastructure and how such controlled platoons can be used improve overall traffic conditions. It will be argued that the average total variation of traffic density can be reduced and thereby creating incentives for platooning beyond fuel savings and driver support. Extensive experiments done on European highways will illustrate system performance and safety requirements. The presentation will be based on joint work with collaborators at KTH and at the truck manufacturers Scania and Volvo.

Biography: Karl H. Johansson is Professor at the School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology. He received MSc and PhD degrees from Lund University. He has held visiting positions at UC Berkeley, Caltech, NTU, HKUST Institute of Advanced Studies, and NTNU. His research interests are in networked control systems, cyber-physical systems, and applications in transportation, energy, and automation networks. He has received several best paper awards and other distinctions from IEEE, IFAC and ACM. He has been awarded Distinguished Professor with the Swedish Research Council and Wallenberg Scholar with the Knut and Alice Wallenberg Foundation. He has received the Future Research Leader Award from the Swedish Foundation for Strategic Research and the triennial Young Author Prize from IFAC. He is Fellow of the IEEE and the Royal Swedish Academy of Engineering Sciences, and he is IEEE Distinguished Lecturer.

Control of automated vehicles and their influence on traffic

Seminar on October 03, 2019, 2:00 PM at CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Karl H. Johansson


Abstract: Automated and connected road vehicles enable large-scale control and optimisation of the transport system with the potential to radically improve fuel efficiency, decrease the environmental footprint, and enhance safety. In this talk we will focus on automated heavy-duty vehicle platooning, which is currently being implemented and evaluated by several truck manufacturers world-wide. We will discuss how to deploy feedback control of individual platoons utilising the cellular communication infrastructure and how such controlled platoons can be used improve overall traffic conditions. It will be argued that the average total variation of traffic density can be reduced and thereby creating incentives for platooning beyond fuel savings and driver support. Extensive experiments done on European highways will illustrate system performance and safety requirements. The presentation will be based on joint work with collaborators at KTH and at the truck manufacturers Scania and Volvo.

Biography: Karl H. Johansson is Professor at the School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology. He received MSc and PhD degrees from Lund University. He has held visiting positions at UC Berkeley, Caltech, NTU, HKUST Institute of Advanced Studies, and NTNU. His research interests are in networked control systems, cyber-physical systems, and applications in transportation, energy, and automation networks. He has received several best paper awards and other distinctions from IEEE, IFAC and ACM. He has been awarded Distinguished Professor with the Swedish Research Council and Wallenberg Scholar with the Knut and Alice Wallenberg Foundation. He has received the Future Research Leader Award from the Swedish Foundation for Strategic Research and the triennial Young Author Prize from IFAC. He is Fellow of the IEEE and the Royal Swedish Academy of Engineering Sciences, and he is IEEE Distinguished Lecturer.

Segmentation-déconvolution d'images texturées: gestion des incertitudes par une approche bayésienne hiérarchique et un échantillonnage stochastique

Seminar on July 09, 2019, 4:30 PM at CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Jean-François Giovannelli


Résumé : La présentation concerne la déconvolution-segmentation conjointe pour des images présentant des texturées orientées. Les images sont constituées de régions présentant des patchs de textures appartenant à un ensemble de K classes prédéfinies. Chaque classe est modélisée par un champ gaussien piloté par une densité spectrale de puissance paramétrique de paramètres inconnus. Par ailleurs, les labels de classes sont modélisés par un champ de Potts de paramètre est également inconnu. La méthode repose sur une description hiérarchique et une stratégie d'estimation conjointement des labels, des K images texturées, ainsi que des hyperparamètres: niveaux du bruit et des images ainsi que paramètres de texture et du champ de Potts. La stratégie permet de définir des estimateurs optimaux au sens d'un risque joint: maximiseur ou moyenne a posteriori selon les paramètres. Ils sont évalués numériquement à partir d'échantillons de loi a posteriori, eux-mêmes obtenus par un algorithme de Gibbs par bloc. Deux des étapes sont délicates: (1) le tirage des images texturées, gaussiennes de grande dimension, est réalisé par un algorithme de Perturbation-Optimization [a] et (2) le tirage des paramètres des images texturées obtenu par une étape de Fisher Metropolis-Hastings [b]. On donnera plusieurs illustrations numériques notamment en terme de quantification des incertitudes. Le travail est publié dans [c].
[a] F. Orieux, O. Féron and J.-F. Giovannelli, "Sampling high-dimensional Gaussian distributions for general linear inverse problems", Signal Processing Letters, May 2012.
[b] C. Vacar, J.-F. Giovannelli, Y. Berthoumieu, "Langevin and Hessian with Fisher approximation stochastic sampling for parameter estimation of structured covariance" ICASSP 2011.
[b'] M. Girolami, B. Calderhead, "Riemannian manifold Hamiltonian Monte Carlo", Journal of the Royal Statistical Society, 2011.
[c] 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, 2019

Short bio : Jean-François Giovannelli was born in Beziers, France, in 1966. He received the Dipl. Ing. degree from the Ecole Nationale Supérieure de l'Electronique et de ses Applications, Cergy, France, in 1990, and the Ph.D. degree and the H.D.R. degree in signal-image processing from the Universite Paris-Sud, Orsay, France, in 1995 and 2005, respectively. From 1997 to 2008, he was an Assistant Professor with the Universite Paris-Sud and a Researcher with the Laboratoire des Signaux et Systemes, Groupe Problèmes Inverses. He is currently a Professor with the Universite de Bordeaux, France and a Researcher with the Laboratoire de l'Integration du Matériau au Système, Groupe Signal-Image, France. His research focuses on inverse problems in signal and image processing, mainly unsupervised and myopic problems. From a methodological standpoint, the developed regularization methods are both deterministic (penalty, constraints,...) and Bayesian. Regarding the numerical algorithms, the work relies on optimization and stochastic sampling. His application fields essentially concern astronomical, medical, proteomics, radars and geophysical imaging.

Advances in data processing and machine learning in camera networks

Seminar on July 09, 2019, 3:30 PM at CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Hichem Snoussi


Résumé : The aim of this tutorial is to give an overview of recent advances in distributed signal/image processing in wireless sensor networks. Over the past few years, wireless sensor networks received tremendous attention for monitoring physical phenomena and for target tracking in a wide region or a critical infrastructure under surveillance. With such systems, the automatic monitoring of an event or an incident is based on the reliability of the network to provide an efficient and robust decision-making. Applying conventional signal/image techniques for distributed information processing is inappropriate for wireless sensor networks, since the computational complexity scales badly with the number of available sensors and their limited energy/memory resources. For this purpose, collaborative information processing in sensor networks is becoming a very attractive field of research. The sensors have the ability to collaborate and exchange information to ensure an optimal decision-making. In this tutorial, we review recently proposed collaborative strategies for self-localization, target tracking and nonlinear functional estimation (nonlinear regression), in a distributed wireless sensor network. The collaborative strategy ensures the efficiency and the robustness of the data processing, while limiting the required communication bandwidth. Signal processing challenges in mobile ad-hoc sensor networks will also be considered in this tutorial.

En compagnie de ses anciens collègues et doctorants, Ali retrace les moments importants de sa carrière.

Seminar on July 09, 2019, 2:00 PM at CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Ali


En compagnie de ses anciens collègues et doctorants, Ali retrace les moments importants de sa carrière.

15h/15h30 Pause café devant l'amphi Janet

En compagnie de ses anciens collègues et doctorants, Ali retrace les moments importants de sa carrière.

Seminar on July 09, 2019, 2:00 PM at CentraleSupelec (Gif-sur-Yvette) Amphi Janet
Ali


En compagnie de ses anciens collègues et doctorants, Ali retrace les moments importants de sa carrière.

A Bayesian deep learning approach in thermal remote imaging with hyper-resolution

Seminar on July 09, 2019, 10:30 AM at CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Ning Chu


Résumé : Remote monitoring and early warning of thermal source abnormality play more and more important roles in fire prevention for the museums and historical monuments (Notre dame de Paris e.g.), metro and electric vehicle (Tesla e.g.) etc. However, conventional thermal imaging techniques cannot obtain the accurate temperature distribution of thermal sources in the far-fields. This is due to the fact that true temperature of thermal sources, according to heat radiation model, depends on many complex factors such as background temperature, environment humidity and surface emissivity . To solve the above challenge, we propose a Bayesian deep learning approach  in thermal remote imaging with hyper-resolution. And mixture Gaussian priors are employed to model the temperature distribution of thermal sources, as well as background temperature. Meanwhile, sparsity-enforcing prior of temperature gradient is also utilized for spatial hyper-resolution. Moreover, the environment humidity and surface emissivity in heat radiation model can be studied by latent variables in Bayesian Hierarchy Network, so that these two important parameters can be estimated by maximizing the entropy of variational Bayesian inference. Through this Bayesian deep learning framework (sampling-training-updating),  temperature mapping of hot sources can be accurately obtained (about 0.5 degree Celsius variation) as far as 5-10 meters way through a cost-effective infra-red camera (

Short bio : Mr. Ning Chu received the Bachelor in information engineering  from the National University of Defense Technology in 2006. He obtain the master and PhD in automatic signal, and image processing from the University of Paris Sud, France  in 2010 and 2014 respectively. He then won the positions of scientific collaborator in École Polytechnique Fédérale de Lausanne, Switzerland, and senior lecturer in Zhejiang Unviersity. His research interests mainly focus on acoustic source imaging, Bayesian deep learning in condition monitoring and inverse problem applied in super resolution imaging. He has published more than 22 peer-reveiwer journal papers, invited for lectures by top international scientific conferences, own 5 China patents and 6 software copyrights.

Imaging with Electromagnetic Waves and Fields, from Eddy Current to Microwave

Seminar on July 04, 2019, 10:00 AM at CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Yu Zhong


Abstract: Imaging problems with electromagnetic waves and fields are of great interest due to non-intrusive inspection enabled by such imaging methods. In this talk, two major imaging methods in two different frequency bands will mainly be discussed, eddy current imaging at low frequency and microwave imaging at resonant frequency regime. As these two types of problems are nonlinear and unstable, from mathematical perspectives, one will show, in each, how these difficulties are specifically handled.

In the first part, the physical mechanism of eddy current inspection will be discussed, followed by a full description of an inspection system. An imaging method that could work with the measured eddy current signals will then be proposed. It includes a forward model for eddy current interactions with defects, an experimental signal calibration model, a defect model for inversion, and an optimization scheme. It will be shown how these bricks work together to provide imaging results from phaseless eddy current signals.
In the second part, the highly nonlinear inverse scattering problems (ISPs) will be shown how to be efficiently tackled by the recently proposed contraction integral equation for inversion (CIE-I), in both three-dimensional (3-D) problems and 2-D problems with phaseless data. With the CIE-I, the non-linearity of ISPs is largely remedied by suppressing multiple scattering effects within the inversions, without compromising the physical model accuracy. This is very important when handling the computationally costly 3-D ISPs, since  each iteration of inversion might cost many computational resources. Compared to conventional imaging methods with the well-known Lippmann-Schwinger integral equation (LSIE), this new imaging method with CIE-I shows much better performance when tackling both 3-D ISPs and 2-D ones with phaseless data, w.r.t. resolvability against non-linearity and convergence speed.

 

Biography: Yu Zhong received the B.E. and M.E. degrees in electronic engineering from Zhejiang University, Hangzhou, China, in 2003 and 2006, respectively, and the Ph.D. degree in electrical and computer engineering from the National University of Singapore, Singapore, in 2010. He was a Research Engineer and a Fellow with the National University of Singapore, from 2009 to 2013, then involved in a French-Singaporean MERLION Cooperative Program. Since 2014, he has been a Scientist with the Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research, Singapore. He has been regularly invited to the Laboratoire des Signaux et Systèmes (L2S), Gif-sur-Yvette, France, as Senior Scientific Expert once per year since 2012. He was invited as a Visiting Professor to University of Trento, Italy, in June 2018. His current research interests include numerical methods for inverse problems associated with waves and fields, electromagnetic and acoustic modeling with complex materials, and non-destructive testing.

The role of blockchain and IoT in the future of smart cities – A practical approach

Seminar on July 04, 2019, 10:00 AM at CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Mohammad Hammoudeh


Abstract: The advent of communication technologies and smart storage brought the concept of smart cities. One of the key enabling technologies of smart living is the Internet of Things (IoT). The proliferation in IoT applications raised many serious security concerns to citizens, businesses and governments. Recently, blockchain has been advocated to as a solution for secure data storage and sharing.

In this talk, we explore the challenges of the application of blockchain to IoT using a use case from the pharmaceutical sector. We explore how these leading technologies are making cities smarter by making operations efficient, secure and sustainable. In the second half of the talk, we will deliver a live demonstration of CupCarbon U-One, a smart city simulator.

Bio: Mohammad Hammoudeh​ is a Reader in Future Networks and Security. He is the Head of the CfACS IoT Laboratory within the Department of Computing and Mathematics, Manchester Metropolitan University. He has been a researcher in the field of big sensory data communication, mining and visualisation. He is a highly proficient, experienced, and professionally certified cyber security professional, specialising in threat analysis, and information and network security management. His research interests include highly decentralised algorithms, communication, and cross-layered solutions to Internet of Things, and wireless sensor networks.​

Ahcene Bounceur is an associate professor (HDR and qualified for professorship) of Computer Science and Operations Research at the University of Brest (UBO). He is a member of the Lab-STICC Laboratory. He received a Ph.D. in Micro and Nano electronics at Grenoble INP, France in 2007. He received the M.S. degrees from ENSIMAG, Grenoble, France in 2003. From April 2007 to August 2008, he was a postdoctoral fellow at TIMA Laboratory. From September 2007 to August 2008, he was with Grenoble INP, where he was a temporary professor. He has obtained the 3rd place of the Annual IEEE Test Technology Technical Council (TTTC-IEEE) Doctoral Thesis Contest, Berkeley, May 2007. His current research activities are focused on: Tools for simulation of Wireless Sensor Networks (WSN) dedicated to Smart-cities and IoT, parallel models for accelerating simulations and predicting/testing parameters in WSNs, sampling methods for data mining and Big Data. He is the coordinator of the ANR project PERSEPTEUR and the developer of the IoT platform SUIDIA for gestational diabete monitoring.

Décrypter le langage sonore des animaux : De la technologie du signal vers l'éthologie animale et l'éthologie homme animal

Seminar on June 14, 2019, 10:30 AM at CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Fabienne DELFOUR (LEEC Paris 13) et Pascal BETREMIEUX (Dolhom)


Résumé: Depuis plusieurs décennies, l'homme a entretenu des relations spéciales avec le monde des cétacés, et certaines espèces en particulier (grand dauphin, cachalot, orques) chez lesquelles il a pu reconnaitre un niveau plus sophistiqué de communication sonore, associé à des comportements sociaux proches de comportements humains. Les principaux signes de ces formes "d'intelligence  supérieure" à d'autres espèces proviennent des stratégies de communication sonore mises en évidence scientifiquement à l'aide de nouvelles technologies de capteurs et d'algorithmes de traitement du signal. Travaillant sur certaines espèces de dauphins, nous exposerons quelques découvertes récentes obtenues à partir d'un système innovant d'observation audio/vidéo 3D, alimentant les débats, plus ouverts que jamais, sur l'intelligence animale.
Nous exposerons également un projet basé sur la définition de nouveaux modes de communications avec les dauphins. Des nouveaux modèles d'interaction homme-animal sont ainsi proposés pour la recherche scientifique, la santé et le grand public. Nous terminerons avec quelques questions autour de la biodiversité et des nouvelles formes de relations qui doivent être inventées entre l'humanité 4.0  et le règne animal.

Biographies: Fabienne  Delfour est chercheuse HDR associée au laboratoire d’éthologie expérimentale et comparée de l’université Paris 13, responsable des programmes scientifiques au delphinarium du parc Astérix et associée au Wild Dolphin Project.
Pascal Bétrémieux, fondateur de la startup Dolhom, s'intéresse aux applications éthologiques et sociétales des récentes découvertes scientifiques autour de l'intelligence des dauphins. Il envisage des applications concrètes dans le domaine de la santé et de la relation homme animal en général.

Probabilité et Mécanique Quantique: Loi de Bayes, Estimation de paramètres

Seminar on May 09, 2019, 11:00 AM at CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Clément Pellegrini


Abstract. Dans cet exposé nous reviendrons sur le modèle mathématique décrivant l'expérience de Serge Haroche: "quantum non-demolition experiment" pour lequel il a reçu le prix Nobel de Physique. A travers ce modèle nous verrons comment la loi de Bayes apparait naturellement dans le contexte de la mécanique quantique: notamment dans le contexte des mesures indirectes. Nous verrons ensuite comment nous pouvons faire de l'estimation de paramètres sur ces modèles et comment on peut parler de stabilité du filtre sous-jacent. Cet exposé ne demande pas de prérequis de mécanique quantique, nous introduirons les concepts de base nécessaires.

Bio. Clément Pellegrini, Maitre de conférences à l'université Paul Sabatier Toulouse III depuis 2009
Post-doctorat sous la direction de Francesco Petrucionne à Durban 2008-2009
Doctorat sous la direction de Stéphane Attal à l'université Claude Bernard Lyon: thèse soutenue en 2008

Exponential stabilization of open quantum systems

Seminar on April 26, 2019, 10:30 AM at CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Weichao LIANG


Abstract: In view of the rapid development of quantum information science, the interest in developing systematic theories for controlling quantum systems is rapidly increasing. In particular, the concept of quantum feedback control has central importance in engineering of reliable quantum technologies, similar to the classical case.

In this talk, we will review some basic notations of quantum mechanics and introduce the dynamics of open quantum systems under the continuous-time measurements. We will then present our results on feedback exponential stabilization of Spin-1/2 systems.

Bio: Weichao Liang received the B.Sc degree in Telecommunication from XiDian University, China, in 2014 and the M.Sc. degree in Automatic from CentraleSupélec-Université Paris Sud, France, in 2016. He is currently working toward the Ph.D. degree in Laboratoire des Signaux et Systemes, CentraleSupélec-Université Paris Sud-Université Paris Saclay under the supervision of Paolo Mason and Nina Amini. His research interests include stabilization of open quantum systems, stochastic control and non-linear control.

Control and estimation problems in antilock braking systems

Seminar on April 26, 2019, 10:00 AM at CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Missie AGUADO


Abstract: Introduced by Bosch in 1978, the antilock braking system (ABS) is nowadays one of the most important safety systems for wheeled vehicles. The ABS has two main objectives: to prevent the wheels from locking during heavy braking in order to maintain the stability and steerability of the vehicle, and to maximally exploit the tyre-road friction coefficient in order to achieve the shortest possible braking distance.

In this talk we will review the basics of the wheel dynamics and discuss three problems related to the ABS. First, we will address the estimation of the so-called extended braking stiffness, which is defined as the derivative of the friction coefficient between the tyre and the road. Next, using this estimation, we will reformulate the (control) objective of the ABS in terms of the extended braking stiffness and present a novel control algorithm for the ABS.

Finally: we will address the estimation of the wheel’s angular velocity and acceleration from the measurements of an incremental encoder with imperfections, a problem which is often overlooked in the literature and whose solution is essential for the operation of the ABS.

Bio: Missie Aguado was born in Mexico City in 1988. She received her B.Sc. degree in electric and electronic engineering in 2012, and her M.Sc. degree in control engineering in 2015, both with the highest honors from the National Autonomous University of Mexico (UNAM). She is currently working towards her PhD degree in automatic control in Univ. Paris-Saclay under the supervision of W. Pasillas-Lépine and Antonio Loría. Her research interests include nonlinear control and estimation with applications to wheeled vehicles and electrical motors.

S³ seminar :Décomposition spectroscopique en imagerie multispectrale

Seminar on April 06, 2018, 10:30 AM at CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Vincent MAZET and Hassan MORTADA (ICube / équipe IMAGeS / groupe IPSEO, Université de Strasbourg)


La cinématique interne des galaxies est une clé pour comprendre l'histoire de l'Univers. Elle peut être étudiée en analysant les raies du spectre de la galaxie qui sont décalées par effet Doppler. Les observations multispectrales des galaxies permettent donc de mesurer le décalage des raies dans chaque pixel. Par ailleurs, la spectroscopie de photoélectrons est une technologie qui permet de suivre l'état d'un système en fonction du temps. Les données produites sont une séquences de spectres dont les raies évoluent au cours des acquisitions. Ces deux applications ont en commun des signaux spectroscopiques, répartis dans l'espace ou le temps, et dont les raies évoluent lentement en longueur d'onde, en intensité et en forme.

Un grand nombre de travaux portent sur la décomposition d'un unique spectre, mais aucune approche ne permet la décomposition simultanée de plusieurs spectres présentant une évolution lente des raies. Le projet DSIM, financé par l'ANR, a permis de développer des outils pour décomposer ces spectres, c'est-à-dire pour estimer le nombre et les paramètres des raies dans les spectres. La décomposition spectroscopique est considérée comme un problème inverse : les raies sont modélisées par une fonction paramétrique dont les paramètres sont à estimer.

Nous avons principalement exploré deux manières d'introduire et de traiter l'information d'évolution lente de ces paramètres. D'une part, le problème a été établi dans le cadre bayésien et l'utilisation de l'algorithme RJMCMC a permis d'obtenir de très bon résultats. D'autre part, afin accélérer le temps de calcul de cette première méthode, nous avons considéré le problème comme une séparation de sources retardées et paramétriques. Le défi réside dans le fait que les sources sont extrêmement corrélées. Un schéma de moindres carrés alternés incluant un algorithme d'approximation parcimonieuse a pour cela été conçu.

Biography: Vincent Mazet a soutenu sa thèse à l'Université de Nancy en 2005. Depuis 2006, il est maître de conférences à l'Université de Strasbourg et effectue ses recherches dans le laboratoire ICube. Ses recherches portent sur les problèmes inverses en traitement d'images, en utilisant en particulier des approches bayésiennes ou par approximation parcimonieuse, et en les appliquant à la spectroscopie, à la télédétection ou à l'imagerie hyperspectrale astronomique.

Hassan Mortada a eu son licence en électronique à l’Université Libanaise (UL) en  2013. Il a obtenu son master en 2015 à l’Université de Brest (master recherche signaux et circuits).  Depuis 2015, il prépare sa thèse à l’Université de Strasbourg, ICUBE. Ses thématiques de recherche concernent les problèmes inverses et l'approximation parcimonieuse appliquée aux données spectroscopiques.

S³ seminar : Chauves-souris, écholocation et neuroscience computationnelle : que nous disent les bornes de Cramer-Rao ?

Seminar on March 09, 2018, 10:30 AM at CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Didier MAUUARY (BLUEBAT)


L’écholocation chez les mammifères, découverte dans les années 50, n’a pas fini de nous surprendre. L’intérêt pour la discipline, qu’on aborde désormais sur l’angle du sonar/radar cognitif (coté traitement du signal et ingénierie système) ou des neurosciences computationnelles (du côté des biologistes, éthologues ou des neurosciences) semble au contraire connaitre un regain d’intérêt ces dernières années, notamment dans une perspective bayésienne.

Nous montrons dans cet exposé des résultats récents obtenus lors de la mise au point d’un des premiers systèmes opérationnels de géolocalisation acoustique dynamique de l’animal dans son environnement naturel. Dans ce travail, nous exploitons en premier lieu la théorie de Fischer et les célèbres bornes de Cramer-Rao pour affronter, d’une part, la problématique de l’incertitude temps-fréquence intrinsèque aux formes d’onde émises par l’animal et, d’autre part, analyser la problématique de l’adaptation de son système sonar en fonction de l’objectif de perception et des contraintes environnementales.

Ces travaux reprennent les premières tentatives de trajectographie acoustique passive de l’animal par Yves Tupinier et Patrick Flandrin, il y a une quarantaine d’année. Ils dévoilent désormais des résultats concrets particulièrement novateurs sur le plan biologique, comportemental et/ou neurologique. Par ailleurs, la portée industrielle de ces travaux est stratégique à l’heure où nous cherchons désormais à développer des systèmes de drone capable de voler en milieu confiné, ce que la chauve-souris sait faire admirablement, les yeux fermés…

Biography: Didier Mauuary, Ingénieur Centrale Paris (89), spécialité physique de l’océan et de l’atmosphère et Docteur INPG (94) débute ses travaux en acoustique sous-marine pour développer des méthodes d’observation physique globale à l’échelle climatique. Il poursuit ses travaux de recherche en collaboration avec l’université Carnegie Mellon de Pittsburgh et l’institut des sciences de la Mer de Kiel, ce qui l’amène à cosigner un article dans le magazine Nature. Il poursuit ensuite sa carrière dans l’industrie du SONAR, principalement dans le secteur de la Défense et publie une dizaine d’articles scientifiques dans les revues et conférences internationales. Il crée en 2010 la première startup française dont le programme de R&D est principalement axé sur la chauve-souris.

S³ seminar : Fourier transforms of polytopes and their role in Number Theory and Combinatorics

Seminar on December 21, 2017, 11:30 AM at CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Sinai Robins, (University of Sao Paulo, Sao Paulo, Brasil and Brown University, Providence, USA)


We introduce the topic of the Fourier transform of a Euclidean polytope, first by examples and then by more general formulations.  Then we point out how we can use this transform (and the frequency space) to analyze the following problems:
1.  Compute lattice point enumeration formulas for polytopes
2.  Relate the transforms of polytopes to tilings of Euclidean space by translations of a polytope

We will give a flavor of how such applications arise, and we point to some conjectures and applications.

S³ seminar : On the polynomial part of a restricted partition function

Seminar on December 21, 2017, 10:30 AM at CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Karl Dilcher, (Dalhousie University, Halifax, Canada)


We prove an explicit formula for the polynomial part of a restricted
partition function, also known as the first Sylvester wave. This is achieved by way of some identities for higher-order Bernoulli polynomials, one of which is analogous to Raabe's well-known multiplication formula for the ordinary Bernoulli polynomials. As a consequence of our main result we obtain an asymptotic expression of the first Sylvester wave as the coefficients of the restricted partition grow arbitrarily large.
(Joint work with Christophe Vignat).

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