Laboratory of
signals and systems

The laboratory

The Laboratory of Signals and Systems (L2S, UMR 8506) is a French research laboratory created in 1974, located in Paris-Saclay University, and jointly operated by the CNRS, CentraleSupélec and the University of Paris-Saclay.

Research at L2S focuses on fundamental and applied mathematical aspects of control theory, AI, data science, information, signal and image processing, communication, and network theory.

The laboratory was evaluated by HCERES in 2018 and will be evaluated again in 2023.

Key figures


faculty members


PhD students


publications in 2020


Research fields

Systems and Control

Our research in area of control systems covers both methodological developments and concrete applications. It addresses analysis, modeling, and control problems in fields ranging from biology to power systems engineering. Methodological developments concern, among others, hybrid systems, delay systems, and model predictive control, with a particular emphasis on nonlinear systems. These activities are often carried […]
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Signal processing and Statistics

Research activities in Signal processing and Statistics are inspired from data processing challenges in various application fields such as health engineering, nondestructive testing of materials, acoustics, remote sensing, astrophysics, transportation, electrical and mechanical engineering. Our research aims at proposing solutions to big and possibly heterogeneous data analysis, statistical learning, data mining, temporally and spatially correlated […]
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Telecommunications and Networks

The Telecommunications and Networks activity carries out fundamental research in the field of Networks and Telecommunications. In terms of applications, the main areas of interest include wireless networks, vehicular networks, but also emerging subjects such as synergy between communication networks and smart grids. The Telecommunications and Networks activity brings together skills at the “lower layers” […]
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France is developing a research and innovation strategy to develop information technologies in the field of intelligent electrical power systems (or Smart Grids), an interdisciplinary field par excellence. The applications include power generation systems (e.g. from renewable energy sources), large interconnected power transmission networks, local distribution networks, on-board electrical systems and land-based electric vehicles in […]
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Health & biology

The “data revolution” is impacting all areas of “health and life” and offers a field of application where statistics/machine learning, image processing, control theory and data protection find their full meaning. The “health and life” interdisciplinary axis aims at promoting existing actions and encourage new interdisciplinary collaborations in the field of biology and medicine. Examples […]
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Industry 4.0

Industry of the future, in the wave of the current fourth industrial revolution, will be powered by the drastic increase in the information processing capacities, the communication networks expansion, the development of modeling and simulation tools, and the advances of management and logistics processes. In this context, the “Industry of the future” interdisciplinary axis federates […]
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INS2I: Portrait BD de Nina Amini : le contrôle du monde quantique

Au travers de 12 portraits de chercheuses, enseignantes-chercheuses et ingénieures dans les sciences du numérique, croquées par le crayon de […]
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Séminaire de Ravi N. Banavar

10h00-11h00 – Salle des séminaires (L2S) A Geometric PID Control law for Stabilization of Nonholonomic Mechanical Systems on Lie Groups […]
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Soutenance de thèse de Daouda DIAKITE

Synthèse de haut niveau sur FPGA pour problèmes inverses : application à la tomographie et à la radioastronomie. Titre anglais […]
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Avis de soutenance Yarui ZHANG

soutient sa thèse de doctorat de l’Université Paris-Saclay, École doctorale Electrical, Optical, Bio-Physics and Engineering, Spécialité Génie électrique, Graduate School […]
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UQSay #52

The fifty-second UQSay seminar on UQ, DACE and related topics will take place online on Thursday afternoon, December 15, 2022. […]
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Avis de Soutenance Monsieur Ian MENEGHEL DANILEVICZ

Soutiendra publiquement ses travaux de thèse intitulés Modèles linéaires mixtes robustes, méthodes alternatives de régression quantile pour les données de […]
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