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DTSTART;TZID=Europe/Paris:20260325T153000
DTEND;TZID=Europe/Paris:20260325T170000
DTSTAMP:20260408T200331
CREATED:20260320T191304Z
LAST-MODIFIED:20260320T191304Z
UID:9946-1774452600-1774458000@www.etis-lab.fr
SUMMARY:ETIS-Cell seminar - Camille Simon Chane
DESCRIPTION:We are delighted to welcome Camille Simon Chane over Teams for an ETIS-Cell seminar\, which will occur on Wednesday\, 25 March 2026. Room D331 at ENSEA has been booked for colleagues who would like to see the presentation on a bigger screen. \nTitle: Acquisition- and data-driven processing for demanding interdisciplinary applications: from cultural heritage to biodiversity assessment \nAbstract: This talk presents an overview of my work in computer vision for interdisciplinary applications in cultural heritage and public health\, working with unconventional acquisition systems such as event-based cameras. A particular focus will be given to the evolution and positioning of this work as it pertains to planetary boundaries. \nBio: Camille Simon Chane received her MSc in Electrical and Computer Engineering from the Georgia Institute of Technology in 2008\, followed in 2009 by the French Engineering diploma from ENSEA. She earned her PhD in Imaging Instrumentation and Computer Vision from the University of Burgundy in 2013\, where her research focused on the registration of featureless 3D and multispectral data. From 2013 to 2014\, she worked at the Cité de la Musique\, developing a luminescence multispectral camera for the study of violin varnishes. She then joined the Vision and Natural Computation team at the Institut de la Vision\, where she expanded her expertise in event‑based data processing. Since 2017\, she has been an Associate Professor at ENSEA\, conducting her research within the Cell team of the ETIS laboratory. Her work centers on data processing from unconventional sensors\, with applications in public health and cultural heritage. For example\, she contributes to projects assessing the conservation state of book bindings in heritage libraries and developing insect recognition methods based on wing morphology. She is focusing on insect recognition for the 2025−2026 academic year through a sabbatical at Theoretical Ecology Department at CSIC−CEAB. \nLink: https://teams.microsoft.com/meet/33442086490136?p=D06BGQX6z0iCVGvFeA\nMeeting ID: 334 420 864 901 36\nPasscode: Rg3Ka2Wm
URL:https://www.etis-lab.fr/event/etis-cell-seminar-camille-simon-chane/
LOCATION:Online
CATEGORIES:ETIS,Seminar
ATTACH;FMTTYPE=image/jpeg:https://www.etis-lab.fr/wp-content/uploads/2023/10/camillesimonchane_nb.jpg
ORGANIZER;CN="St%C3%A9phane Zuckerman":MAILTO:stephane.zuckerman@etis-lab.fr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20260318T140000
DTEND;TZID=Europe/Paris:20260318T150000
DTSTAMP:20260408T200331
CREATED:20260317T095613Z
LAST-MODIFIED:20260317T095613Z
UID:9923-1773842400-1773846000@www.etis-lab.fr
SUMMARY:Séminaire SmartGait Lab : Dr Zaid Akram
DESCRIPTION:[Séminaire SmartGait Lab] Les surfaces intelligentes (RIS) pour l’analyse radar de l’activité humaine\nL’équipe SmartGait Lab a le plaisir de vous inviter à son prochain séminaire de recherche intitulé : « L’apport des surfaces intelligentes réfléchissantes (RIS) dans l’analyse radar de l’activité humaine ». \nPour cette session\, nous aurons l’honneur d’accueillir le Dr Zaid Akram\, chercheur à l’Université de Glasgow et expert de ces technologies. Le Dr Zaid partagera ses travaux sur l’optimisation de l’environnement électromagnétique au service du suivi biométrique sans contact. \n📍 Informations pratiques \n\nDate : Mercredi 18 mars\nHeure : 14h00 – 15h00\nLieu : ENSEA\, salle D331\nVisioconférence : https://teams.microsoft.com/meet/37048590102227?p=gkBIesu1Z9B51Heeiy\nIntervenant : Dr Zaid Akram (Glasgow University)
URL:https://www.etis-lab.fr/event/seminaire-smartgait-lab-dr-zaid-akram/
LOCATION:ENSEA\, salle 331\, 6 avenue du Ponceau\, Cergy\, 95000\, France
CATEGORIES:Seminar
ORGANIZER;CN="Alexandre Bordat":MAILTO:alexandre.bordat@ensea.fr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20260219T150000
DTEND;TZID=Europe/Paris:20260219T160000
DTSTAMP:20260408T200331
CREATED:20260119T160023Z
LAST-MODIFIED:20260213T132721Z
UID:9735-1771513200-1771516800@www.etis-lab.fr
SUMMARY:ETIS seminar: Michel Bourdellès
DESCRIPTION:Intégration de services au processus de réalisation de systèmes pour la validation automatique d’exigences de sécurité\nDr. Michel Bourdellès \nMots clefs : Security\, Model-Based Systems Engineering (MBSE)\, Model-Based Product Line Engineering (MBPLE)\, System of Systems Engineering\, systems architecting\, Early Validation and Audit. \nRésumé : La mise en œuvre des mécanismes de protection adéquats de flux de données des systèmes\, traduits en exigences de sécurité issues d’une analyse de risque\, est une contrainte forte de la réalisation des produits. Ces mécanismes\, logiciels et matériels\, doivent garantir la validation des contraintes initiales de sécurité sur le produit final avant mise en production. Nous listons un ensemble de besoins que doit satisfaire le processus industriel de réalisation produit afin de prendre au mieux en compte ces exigences dans le produit. Nous proposons un ensemble de services pour compléter les processus industriels basés sur la validation d’exigences opérationnelles afin d’analyser la correction des choix de conception système par rapport aux exigences de sécurité\, et produire automatiquement du code de sécurité. La solution proposée prend aussi en compte les contraintes liées au processus de réalisation lui-même en assurant le besoin d’en connaître par la protection à l’accès par les parties prenantes de l’information confidentielle\, étendu à la réalisation de lignes de produits\, ainsi que de l’application de la solution à des systèmes de systèmes. \nShort Bio: Michel Bourdellès est enseignant chercheur en cybersécurité à l’ESIEE-IT\, associé à l’équipe SecReizh de l’Université Bretagne Sud. Ses thèmes de recherche\, influencés par plus de vingt ans d’activités comme ingénieur dans un grand groupe de la défense\, portent sur la validation automatique d’exigences de sécurité de systèmes industriels. \n 
URL:https://www.etis-lab.fr/event/etis-seminar-michel-bourdelles/
LOCATION:CY Cergy Paris Université\, site de Saint-Martin\, 2 Av. Adolphe Chauvin\, Pontoise\, 95300\, France
CATEGORIES:ETIS,Seminar
ORGANIZER;CN="Aikaterini Tzompanaki":MAILTO:aikaterini.tzompanaki@ensea.fr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20260129T133000
DTEND;TZID=Europe/Paris:20260129T150000
DTSTAMP:20260408T200331
CREATED:20260123T075216Z
LAST-MODIFIED:20260123T075216Z
UID:9749-1769693400-1769698800@www.etis-lab.fr
SUMMARY:Séminaire DATA&AI : Issam Falih
DESCRIPTION:Apprentissage multimodal frugale : alignement par transport optimal\, explicabilité par concepts et déploiement Edge\nRésumé :\nLes architectures d’apprentissage profond constituent aujourd’hui l’état de l’art pour l’analyse et la fusion de données multimodales. Leur déploiement effectif dans des environnements ouverts soulève encore de nombreuses questions quant à leur fiabilité et leur transparence. En particulier\, si ces modèles excellent en conditions contrôlées\, plusieurs travaux ont mis en évidence leur sensibilité aux dérives distributionnelles (concept drift) et leur opacité décisionnelle\, limitant leur usage dans des contextes critiques. \nDans cette présentation\, je traite dans un premier temps\, des problématiques d’alignement et de fusion multimodale ou je présente le Transport Optimal Hiérarchique comme un levier géométrique pour l’alignement de structures dans un cadre non supervisé. Dans un deuxième temps\, j’aborde l’explicabilité des réseaux de neurones à travers les modèles à goulot de concepts (CBM). Je présente une architecture hybride (KL-CBM) où un classifieur dense est aligné sur un module probabiliste. Enfin\, je conclue avec des applications réelles notamment de l’inférence distribuée sur systèmes embarqués (Edge AI). \nLien de connexion :\nSeminaire Issam Falih | Meeting-Join | Microsoft Teams \n 
URL:https://www.etis-lab.fr/event/seminaire-dataai-issam-falih/
LOCATION:Online
CATEGORIES:Seminar
ORGANIZER;CN="Vassiis Christophides":MAILTO:vassilis.christophides@ensea.fr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20260114T140000
DTEND;TZID=Europe/Paris:20260114T153000
DTSTAMP:20260408T200331
CREATED:20260106T105212Z
LAST-MODIFIED:20260106T105212Z
UID:9664-1768399200-1768404600@www.etis-lab.fr
SUMMARY:Data&AI Seminar - Khalil Bachiri
DESCRIPTION:Title: Multimodal and Heterogeneous Graph Learning for Robust\, Explainable and Frugal Intelligent Systems \nAbstract:\nThe increasing availability of heterogeneous and multimodal data poses significant challenges for the design of modern intelligent systems\, particularly in terms of representation\, fusion\, robustness\, explainability\, and computational frugality. These challenges become even more critical when data are structured through complex and evolving relational graphs\, as is often the case in real-world applications. In this presentation\, I will introduce my research contributions on multimodal and heterogeneous graph learning\, developed during my PhD\, with the objective of designing models capable of understanding\, reasoning\, and learning from interacting modalities. I will present graph-based and topology-aware learning architectures that explicitly model modality heterogeneity\, inter-modal dependencies\, and structural relations\, while relying on adaptive fusion\, alignment mechanisms\, and attention-based reasoning to improve robustness\, stability\, and interpretability. These approaches have been validated on real-world recommendation and decision-support scenarios and have led to several international publications. Finally\, I will outline my research perspectives\, aiming to further develop robust\, energy-efficient\, and explainable multimodal intelligent systems\, including responsible AI\, multimodal platforms\, and low-footprint learning for complex environments. \nShort Bio:\nKhalil Bachiri is a Doctor in Artificial Intelligence from CY Cergy Paris Université (ETIS\, CNRS UMR 8051)\, where he is currently an ATER. His research focuses on multimodal learning and heterogeneous graph learning\, topology-aware models\, and explainable AI\, with an emphasis on robustness\, frugality\, and multimodal reasoning for recommendation and decision-support systems. He has published in international journals and conferences. He also worked as an AI Research Engineer at CNRS and has been a visiting researcher at LIPN (Université Sorbonne Paris Nord). \n 
URL:https://www.etis-lab.fr/event/dataai-seminar-khalil-bachiri/
LOCATION:Online
CATEGORIES:Seminar
ORGANIZER;CN="Vassiis Christophides":MAILTO:vassilis.christophides@ensea.fr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20251120T150000
DTEND;TZID=Europe/Paris:20251120T160000
DTSTAMP:20260408T200331
CREATED:20251118T145535Z
LAST-MODIFIED:20251118T145646Z
UID:9623-1763650800-1763654400@www.etis-lab.fr
SUMMARY:ETIS seminar: Physical layer security for 6G
DESCRIPTION:We are pleased to invite you to the next ETIS lab seminar\, which will take place this Thursday\, after the PILE at ENSEA.\n\nDate: 20/11/2025\nTime: 14h30 (after the PILE)\nPlace: AMPHI at ENSEA (or online using the link for the PILE)\n\nArsenia Chorti\n\n\nTitle: Physical layer security for 6G\n\nAbstract: Physical-layer security (PLS) is increasingly regarded as a promising component of sixth-generation (6G) communication systems\, owing to its potential to address stringent delay\, power\, and computational constraints. Motivated by these considerations\, this talk pursues two main objectives. First\, we revisit the fundamental security requirements for authentication and key agreement (AKA)\, and examine how these requirements can be translated into concrete PLS design goals. Second\, we present novel AKA mechanisms that leverage trustworthy physical features—such as the angle of arrival in digital-array multiple-input multiple-output systems—as well as machine learning techniques to enable fast\, low-overhead AKA protocols that are provably robust against both passive and active adversaries. Finally\, we outline prospective use cases and research directions for PLS within emerging 6G networks.\n\n\nBio: Arsenia Chorti is a Professor at the École Nationale Supérieure de l’ Électronique et de ses Applications (ENSEA) at the ETIS Lab UMR 8051 and a Visiting Scholar at Princeton University. Her research spans the areas of wireless communications and wireless systems security for 5G and 6G\, with a particular focus on physical layer security. Current research topics include: context aware security\, multi-factor authentication protocols\, 5G / 6G and IoT\, anomaly detection\, machine learning for communications\, new multiple access techniques and scheduling. She is a Senior IEEE Member\, has served as Associate Editor in Chief of the IEEE ComSoc Best Readings\, of the IEEE INGR on Security and Chair of the IEEE Focus Group on Physical Layer Security\, while she has also served in the IEEE P1940 Standardization Workgroup on Standard profiles for ISO 8583 authentication services and has served as a member of the IEEE Teaching Awards Committee. She is currently a Member of various ITU Working Groups and has participated in the reduction of the ITU report M.2516-0 on Future technology trends of Terrestrial International Mobile Telecommunications Systems Towards 2030 and Beyond (sections on trustworthiness).
URL:https://www.etis-lab.fr/event/etis-seminar-physical-layer-security-for-6g/
LOCATION:ENSEA Amphi Watteau\, 6 avenue du Ponceau\, CERGY\, 95014\, France
CATEGORIES:ENSEA,ETIS,Seminar
ATTACH;FMTTYPE=image/jpeg:https://www.etis-lab.fr/wp-content/uploads/2022/01/arsenia_chorti.jpg
ORGANIZER;CN="Aikaterini Tzompanaki":MAILTO:aikaterini.tzompanaki@ensea.fr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20251016T153000
DTEND;TZID=Europe/Paris:20251016T163000
DTSTAMP:20260408T200331
CREATED:20251009T073123Z
LAST-MODIFIED:20251009T073123Z
UID:9387-1760628600-1760632200@www.etis-lab.fr
SUMMARY:ETIS Seminar - Balancing Imbalanced Classification Problems: An Adjustment to the k-Nearest-Neighbor Classifier
DESCRIPTION:On Thursday October 16th at 15h30\, Prof. Arthur Zimek\, Southern Denmark University will give a seminar at the amphitheater E1\, building E (St. Martin). The presentation is expected to last about 45min. Professor Zimek is visiting ETIS for the period of 14-17 October; do not hesitate to contact him if you wish to meet with him. \nTitle: Balancing Imbalanced Classification Problems: An Adjustment to the k-Nearest-Neighbor Classifier\nAbstract: Fairness and bias issues in classification are particularly prevalent when the numbers of examples for different classes are out of proportion. In machine learning this is known as the problem of imbalanced classification. While it is well known that recall rather than precision is the performance measure to optimize in imbalanced classification problems\, most existing methods that adjust for class imbalance do not particularly address the optimization of recall. In this talk\, we discuss an elegant and straightforward variation of the k-nearest-neighbor classifier to balance imbalanced classification problems internally in a probabilistic interpretation and show how this relates to the optimization of the recall. \nArthur Zimek\, Southern Denmark University\, Dr. rer. nat. habil.\nHead of Section\, Professor\, Data Science\nDepartment of Mathematics and Computer Science\nUniversity of Southern Denmark (SDU) \nShort Bio:\nArthur Zimek is Full Professor and Head of the Data Science and Statistics section in the Department for Mathematics and Computer Science (IMADA) at University of Southern Denmark (SDU)\, in Odense\, Denmark. Previous positions were are LMU Munich\, Germany\, TU Wien\, Austria\, and University of Alberta\, Edmonton\, Canada. Several awards include the ”SIGKDD Doctoral Dissertation Award (runner-up)” in 2009\, the ”Best Demonstration Paper Award” at SSTD 2011\, the ”Best Research Paper Award” at SDM 2024\, and a listing in the ACM Computing Reviews ”21st Annual Best of Computing” (2016). His research interests include ensemble techniques for unsupervised learning\, clustering\, outlier detection\, high dimensional data\, and explainable AI\, developing data mining methods as well as evaluation methodology. He serves as associate editor for the Springer Data Mining and Knowledge Discovery journal and the Springer Machine Learning journal. \n  \n  \n 
URL:https://www.etis-lab.fr/event/etis-seminar-balancing-imbalanced-classification-problems-an-adjustment-to-the-k-nearest-neighbor-classifier/
LOCATION:CY Cergy Paris Université – St-Martin -amphi E1\, 2 avenue Adolphe-Chauvin\, Pontoise\, 95300\, France
CATEGORIES:ETIS,Seminar
ATTACH;FMTTYPE=image/jpeg:https://www.etis-lab.fr/wp-content/uploads/2025/10/arthur_zimek.v01.jpg
ORGANIZER;CN="Aikaterini Tzompanaki":MAILTO:aikaterini.tzompanaki@ensea.fr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20250618T140000
DTEND;TZID=Europe/Paris:20250618T160000
DTSTAMP:20260408T200331
CREATED:20250606T143906Z
LAST-MODIFIED:20250606T144830Z
UID:9238-1750255200-1750262400@www.etis-lab.fr
SUMMARY:Cultural Heritage Seminar | Jon Hardeberg and Nistor Grozavu
DESCRIPTION:The next ETIS Tandem seminar will take place on Wednesday June 18th at 2 pm\, in the Curium\, at ENSEA and on zoom (link below). \nJon Yngve Hardeberg from the NTNU (Norwegian University of Science and Technology\, Colourlab) and Nistor Grozavu (ETIS UMR 8051) will talk about their work on Cultural Heritage\, abstracts are given below. \n  \nJon Yngve Hardeberg\nNTNU − Norwegian University of Science and Technology\,\nColourlab\, Department of Computer Science\, N-2815 Gjøvik\, Norway\nSpektralion AS\, N-2815 Gjøvik\, Norway \nSpectral Imaging for Cultural Heritage: Past\, Present\, and Future\nDuring the last few decades\, spectral imaging has proven to be a very useful technology for the precise documentation and non-destructive analysis of tangible cultural heritage objects [1-5]. With spectral imaging we here include various imaging technologies which allow to measure the spectral reflectance of the objects at a large number of spatial locations of the object in one operation. These technologies vary greatly in key parameters such as spatial resolution (number of pixels)\, spectral resolution (number of channels)\, cost\, and time and complexity required to capture high quality images. \nIn this talk we will first introduce the principles of spectral imaging\, before discussing how this type of imaging can be useful in the field of cultural heritage [3\,4]. Then we will present and discuss examples of our recent and ongoing research in this field\, for instance on the topics of pigment mapping in paintings [2\,5\,6\,7]\, hyperspectral analysis of stained glass windows [8]\, analysis of historical textile fragments from the Viking age\, and visualization of hyperspectral images. Finally\, considering the challenging task of properly assessing the quality of a spectral image [3\,9]\, we will discuss the question of how many spectral channels we actually need in a spectral imaging system [10\,11]. \n  \nNistor Grozavu\nETIS UMR 8051\, CY Cergy Paris University\, ENSEA\, CNRS \nUsing multimodal AI to support the preservation of Cultural Heritage under Climate Change\nHeritage materials are increasingly vulnerable to the effects of climate change. Fluctuations in temperature\, humidity\, and other environmental factors can accelerate the degradation of monuments\, yet predicting this weathering remains complex due to the wide range of influencing variables i.e. material properties\, conservation conditions\, and human activity among them. In this talk\, we will explore how artificial intelligence\, and in particular multimodal machine learning\, can help address this challenge. By integrating diverse types of data i.e. scientific images\, in situ sensor readings\, and environmental records\, we aim to better understand and anticipate material deterioration across time and context. Our work focuses on three French heritage sites: Strasbourg Cathedral\, the Bibracte archaeological area\, and the Saint-Pierre Chapel. These sites serve as case studies for developing AI models capable to predict a degradation index under different climate scenarios and opens new perspectives for long-term cultural heritage conservation planning. \n  \nReferences\n[1] H. Maître\, F. Schmitt\, J.-P. Crettez\, Y. Wu and J. Y. Hardeberg\, Spectrophotometric Image Analysis of Fine Art Paintings\, Proc. 4th Color Imaging Conference\, p. 50-53\, Scottsdale\, Arizona\, 1996 \n[2] J. Y Hardeberg\, S. George\, F. Deger\, I. Baarstad\, and J. E. Palacios\, Spectral Scream: Hyperspectral image acquisition and analysis of a masterpiece. In “Public paintings by Edvard Munch and some of his contemporaries. Changes and conservation challenges\,” Archetype Publications\, London\, 2015 \n[3] S. George\, J.Y. Hardeberg\, J. Linhares\, L. MacDonald\, C. Montagner\, S. Nascimento\, M. Picollo\, R. Pillay\, T. Vitorino\, E. K. Webb\, A Study of Spectral Imaging Acquisition and Processing for Cultural Heritage\, in “Digital Techniques for Documenting and Preserving Cultural Heritage\,” Arc Humanities Press\, 2017\, p. 100-130 \n[4] R. Pillay\, J.Y Hardeberg\, S. George\, Hyperspectral Imaging of Art: Acquisition and Calibration Workflows\, Journal of the American Institute for Conservation\, 58(1-2)\, 3-15\, 2019. \n[5] H. Deborah\, S. George\, J. Y. Hardeberg\, Spectral-divergence based pigment discrimination and mapping: A case study on The Scream (1893) by Edvard Munch. Journal of the American Institute for Conservation\, 58(1-2)\, 90-107\, 2019 \n[6] D. J. Mandal\, H. Deborah\, S. George and J. Y. Hardeberg\, “Unsupervised Clustering for Works of Art Using Hyperspectral Imaging: A Case Study on Edvard Munch’s Self-Portrait (1905)\, 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)\, 2023 \n[7] N. Eckertz\, H. Deborah\, J. Y. Hardeberg\, and I. C. A. Sandu\, Spatially Constrained Hyperspectral Pigment Mapping Using Watershed Segmentation\, 14th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS) 2024 \n[8] A. Babini\, S. George\, T. Lombardo\, and J. Y. Hardeberg. Acquisition strategies for in-situ hyperspectral imaging of stained-glass windows: case studies from the Swiss National Museum. Heritage Science\, 11:74\, 2023 \n[9] R. Shrestha\, R. Pillay\, S. George\, J. Y. Hardeberg\, Quality evaluation in spectral imaging – Quality factors and metrics. Journal of the International Colour Association\, 10 p. 22-35\, 2014 \n[10] A. Alsam\, D. Connah\, J. Hardeberg\, Multispectral Imaging: How Many Sensors Do We Need? Journal of Imaging Science and Technology\, 2006\, pp 45 – 52. \n[11] M. Amiri\, G. Trumpy\, “Is Multispectral enough” An evaluation of the performance of multispectral images in pigment unmixing task\,” Proc. London Imaging Meeting\, 2024 \n 
URL:https://www.etis-lab.fr/event/cultural-heritage-seminar-jon-hardeberg-and-nistor-grozavu/
LOCATION:ENSEA\, Curium\, avenue du Ponceau\, Cergy\, 95014\, France
CATEGORIES:ETIS,Seminar
ATTACH;FMTTYPE=image/png:https://www.etis-lab.fr/wp-content/uploads/2025/06/ETIS_seminaire_20250618.png
ORGANIZER;CN="Camille Simon Chane":MAILTO:camille.simon-chane@ensea.fr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20250325T143000
DTEND;TZID=Europe/Paris:20250325T153000
DTSTAMP:20260408T200331
CREATED:20250311T162315Z
LAST-MODIFIED:20250311T162315Z
UID:9046-1742913000-1742916600@www.etis-lab.fr
SUMMARY:Data&AI Seminar : Ozgun Pinarer
DESCRIPTION:Titre : Analyse et Prévision de Données Météorologiques Distribuées Utilisant l’Apprentissage Fédéré et TinyML\nRésumé :\nCe séminaire présentera une étude approfondie sur l’application de l’apprentissage fédéré aux systèmes embarqués à ressources limitées dans les stations météorologiques. L’objectif principal est d’évaluer la performance des modèles d’apprentissage local et fédéré en tenant compte de critères tels que la précision\, la consommation d’énergie et l’utilisation de la mémoire. Notre approche intègre des techniques d’apprentissage automatique et profond pour traiter des données météorologiques collectées à partir de stations en Corse. Ce séminaire abordera la méthodologie adoptée\, les défis liés à l’utilisation de l’apprentissage fédéré sur des systèmes embarqués et les perspectives d’amélioration dans le domaine de l’IoT pour l’analyse météorologique. \nBiographie :\nOzgun Pinarer est maître de conférences et directeur adjoint du département de génie informatique de l’Université Galatasaray à Istanbul\, en Turquie. Il a obtenu son diplôme en génie informatique à l’Université Galatasaray en 2010\, puis a poursuivi ses études en obtenant une maîtrise en génie informatique à la même institution en 2012. En 2017\, il a obtenu son doctorat à l’INSA Lyon\, au laboratoire LIRIS. Ses recherches portent sur l’Internet des Objets (IoT)\, le calcul embarqué optimisé pour le matériel\, la gestion des flux de données des capteurs dans les environnements intelligents\, l’optimisation énergétique des systèmes IoT\, la maintenance prédictive et la gestion des actifs\, ainsi que sur le Tiny ML et l’apprentissage fédéré pour les applications IoT. Il a mené plusieurs projets académiques et industriels dans ces domaines\, notamment sur la gestion des données IoT\, la communication en cas de catastrophe via LoRa\, ainsi que sur l’apprentissage automatique et fédéré appliqué aux systèmes embarqués à faible consommation énergétique. Il organise également\, depuis 2018\, une session spéciale sur les données de santé lors de la conférence IEEE Big Data. Ses travaux récents portent sur l’application de modèles d’apprentissage fédéré aux capteurs météorologiques embarqués\, avec pour objectif d’améliorer la précision des prévisions tout en optimisant les ressources des dispositifs à faible consommation.
URL:https://www.etis-lab.fr/event/dataai-seminar-ozgun-pinarer/
LOCATION:CYU Saint-Martin\, salle de réunion A551\, 2 avenue Adolphe-Chauvin\, Cergy Pontoise\, France
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://www.etis-lab.fr/wp-content/uploads/2025/03/ozgun-pinarer.jpg
ORGANIZER;CN="Hajer Baazaoui":MAILTO:hajer.baazaoui@ensea.fr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20250306T140000
DTEND;TZID=Europe/Paris:20250306T160000
DTSTAMP:20260408T200331
CREATED:20250304T155300Z
LAST-MODIFIED:20250304T155300Z
UID:9025-1741269600-1741276800@www.etis-lab.fr
SUMMARY:IA multimodale et IA générative pour l’indexation vidéo pédagogique
DESCRIPTION:Boris Borzic\, ingénieur de recherche CNRS à ETIS (équipe Data&AI et pôle ingénierie) interviendra à la MSH Mondes de Nanterre sur le thème “IA multimodale et IA générative pour l’indexation vidéo pédagogique“. \nRésumé : \nDans un contexte d’apprentissage adaptatif\, la stratégie « vidéo first » promet une expérience pédagogique plus fluide. Cependant\, la gestion efficace de ces contenus nécessite des outils innovants pour faciliter la navigation et l’accès aux informations clés. L’application d’intelligence artificielle (IA) multimodale et générative peut répondre à ce besoin en permettant une indexation vidéo pédagogique plus efficace. Les questions de révision corrélées à des réponses sous forme d’extrait vidéo\, accompagnées de techniques de RAG (Retrieval Augmented Generation\, génération augmentée de récupération )\, offrent un potentiel significatif pour améliorer l’expérience de l’apprenant et la personnalisation de l’apprentissage. De plus le montage streaming en temps réel sans exportation/importation vidéo constitue une stratégie efficace pour optimiser les ressources et réduire les coûts de bande passante. \nBoris Borzic\, PhD Research engineer\, Ingénieur de recherche CNRS et Fondateur de la startup Deeptech Sequencia (labellisé CNRS RISE)\nETIS – Equipes Traitement de l’Information et Systèmes UMR 8051 / ENSEA – CNRS – CY Cergy Paris Université \nBibliographie :\n \n\nTharsan Senthivel\, Ngoc-Son Vu\, Boris Borzic. Detection Transformer with Diversified Object Queries. IEEE ICIP 2023\, Oct 2023\, Kuala Lampur\, Malaysia. ⟨hal-04304226⟩\nMarianne Froye\, Olivier Belin\, Julien Longhi\, Boris Borzic\, Claudia Marinica\, et al.. L’IDHN : une structure innovante au service de la polysémie du numérique. Humanistica 2020\, May 2020\, Bordeaux\, France. ⟨hal-02875614⟩\nClaudia Marinica\, Julien Longhi\, Nader Hassine\, Abdulhafiz Alkhouli\, Boris Borzic. #Idéo2017 : une plateforme citoyenne dédiée à l’analyse des tweets lors des événements politiques. Extraction et Gestion des Connaissances (EGC)\, Jan 2018\, Paris\, France. ⟨hal-01699423⟩\nDalia Saigh\, Boris Borzic\, Abdulhafiz Alkhouli\, Julien Longhi. A Linguistic Contribution to an Automatic Classification of Communities and their Analysis. Questions de communication\, 2017\, 31\, pp.161 – 182. ⟨10.4000/questionsdecommunication.11097⟩. ⟨hal-01793225⟩\nAbdulhafiz Alkhouli\, Dan Vodislav\, Boris Borzic. Continuous Top-k Queries in Social Networks. CoopIS 2016\, 2016\, Rhodes\, Greece. pp.24 – 42\, ⟨10.1007/978-3-319-48472-3_2⟩. ⟨hal-01417787⟩\n\nInformations pratiques : \nHeure: 6 mars 2025 02:00 PM Paris\nMSH Mondes\, Université Paris Nanterre (Bâtiment Max Weber\, salle de séminaire 1)\nhttps://cnrs.zoom.us/j/91688466917?pwd=8Snj6106A4uV2ALvprhLjefUWI5arz.1\nID de réunion: 916 8846 6917 / Code secret: x5Yk2t \n 
URL:https://www.etis-lab.fr/event/ia-multimodale-et-ia-generative-pour-lindexation-video-pedagogique/
LOCATION:MSH Monde\, 21 allee de l'université bâtiment maw weber\, nanterre\, 92000\, France
CATEGORIES:Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20250303T110000
DTEND;TZID=Europe/Paris:20250303T123000
DTSTAMP:20260408T200331
CREATED:20250217T084116Z
LAST-MODIFIED:20250217T084116Z
UID:9014-1740999600-1741005000@www.etis-lab.fr
SUMMARY:Seminar ETIS-ICI: Rodrigo C. de Lamare
DESCRIPTION:Rodrigo C. de Lamare\, from PUC-RIO\, will give an invited talk on Monday\, March 3rd\, 2025\, 11:00 am\, ENSEA\, room 384. Please find below the details. \nZoom : https://cnrs.zoom.us/j/94161301799?pwd=bTgHYnHGmIqeG3BHPyJEM429aXzVSy.1 \nTitle: Energy-efficient distributed and federated learning for IoT networks \nAbstract:\nIn this presentation\, we will present an energy-efficient distributed learning framework using coarsely quantized signals for Internet of Things (IoT) networks. In particular\, we develop distributed quantization-aware least-mean\, recursive least-squares and federated learning algorithms that can learn parameters in an energy-efficient fashion using signals quantized with few bits while requiring a low computational cost. Moreover\, we develop a bias compensation strategy to further improve the performance of the proposed learning algorithms. We carry out a statistical analysis of the proposed algorithms and derive analytical expressions for predicting the mean-square deviation. A computational complexity evaluation and a study of the power consumption of the proposed and existing techniques are then presented. Numerical results assess the proposed learning algorithms against existing techniques for parameter estimation tasks in IoT networks. \nBiography:\nRodrigo C. de Lamare was born in Rio de Janeiro\, Brazil\, in 1975. He received his Diploma in electronic engineering from the Federal University of Rio de Janeiro in 1998 and the MSc and PhD degrees in electrical engineering from the Pontifical Catholic University of Rio de Janeiro (PUC-Rio) in 2001 and 2004\, respectively. Since January 2006\, he has been with the Communications Research Group\, Department of Electronic Engineering\, University of York\, United Kingdom\, where he is a Professor. Since April 2013\, he has also been a Professor at PUC-RIO. Dr de Lamare is a senior member of the IEEE. He has served as editor for IEEE Wireless Communications Letters\, IEEE Signal Processing Letters and IEEE Transactions on Communications and currently serves as associate editor of IEEE Transactions on Signal Processing. His research interests lie in communications and signal processing\, areas in which he has published over 550 papers in international journals and conferences.
URL:https://www.etis-lab.fr/event/seminar-etis-ici-rodrigo-c-de-lamare/
LOCATION:ENSEA\, salle 384\, 6 avenue du Ponceau\, Cergy\, 95000\, France
CATEGORIES:Seminar
ORGANIZER;CN="Sara Berri":MAILTO:sara.berri@ensea.fr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20250220T144500
DTEND;TZID=Europe/Paris:20250220T163000
DTSTAMP:20260408T200331
CREATED:20250210T100905Z
LAST-MODIFIED:20250210T100905Z
UID:8995-1740062700-1740069000@www.etis-lab.fr
SUMMARY:ETIS Tandem Talk: Paul Gay & Guillaume Renton
DESCRIPTION:Tandem Talk by Paul Gay (UPPA) and Guillaume Renton (ETIS) on Sustainability and Machine Learning. \nPaul Gay | Interactions between sustainibility and machine learning research\nAI is a controversial topic and different visions of sustainibility co-exist in the IT communities. In this talk\, I will describe the state of the art from the GreenIT community to assess environmental impact of IT projects. Although the main ideas\, such as life cycle analysis\, description of embodied impacts and indirect effects have been explored for 10-20 years\, we are only beginning to see them applied to AI systems and projects. \nIn a second part\, I will present two of my current machine learning applications to sustainibility topics. The first one is the use of active learning to detect and classify controversial topic on renewable energies in social networks. The second one is to exploit the technique of early exit\, an interesting tool where the amount of compute depends on the data\, and which find applications in edge-cloud settings. \nGuillaume Renton | Reducing computation costs without jeopardizing precision of Entity Alignment tasks\nIn recent work\, we took interest in the computational cost of one of our entity alignment model\, HybEA. The idea was to provide an efficiency analysis on top of a performance analysis\, which is the main source of comparison between AI models. The efficiency analysis was conducted by using fvcore in order to compute the number of GFLOPS required to train the model. This has led to surprising results\, showing that the initial embedding sizes of the models were oversized. This allowed us to greatly reduce the computational cost of our model with a very small loss of accuracy. \n  \nThe talks will take place in the Curium at ENSEA as well as online:\nhttps://cnrs.zoom.us/j/92031778182?pwd=BcsbEGTQf2JwG8jIUkpaK35fZ1WXUK.1
URL:https://www.etis-lab.fr/event/etis-tandem-talk-paul-gay-guillaume-renton/
LOCATION:ENSEA\, Curium\, avenue du Ponceau\, Cergy\, 95014\, France
CATEGORIES:ETIS,Seminar
ORGANIZER;CN="Camille Simon Chane":MAILTO:camille.simon-chane@ensea.fr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20250207T100000
DTEND;TZID=Europe/Paris:20250207T113000
DTSTAMP:20260408T200331
CREATED:20250124T072146Z
LAST-MODIFIED:20250124T072146Z
UID:8972-1738922400-1738927800@www.etis-lab.fr
SUMMARY:Training neural models using logic: results\, challenges\, and applications
DESCRIPTION:DATA&AI Team Seminar (Online) \nEfi Tsamoura\, Senior Researcher at Samsung AI \nTitle: Training neural models using logic: results\, challenges\, and applications\nAbstract: Neurosymbolic learning (NSL) vows to transform AI by combining the strong induction capabilities of neural models with the strong deduction capabilities of symbolic knowledge representation and reasoning techniques. This talk centers around an NSL problem that has received significant attention lately: training neural classifiers using supervision produced by logical theories. Empirical research has shown the advantages of this learning setting over end-to-end deep neural architectures in multiple aspects\, including accuracy and model complexity. Despite the extensive empirical research\, limited theoretical analysis has been dedicated to understanding if and under which conditions we can learn the underlying neural models. \nThis talk covers this gap by proposing necessary and sufficient conditions\, which ensure that we can learn the underlying models under rigorous guarantees. I will also discuss the relationship between this problem and other known problems in the machine learning literature. Furthermore\, I will present new challenges inherent to this NSL setting and propose solutions to overcome those challenges\, leading to models with substantially higher accuracy. I will conclude this talk with recent applied results and open challenges. \n  \nBio: Efi Tsamoura is a Senior Researcher at Samsung AI\, Cambridge\, UK. In 2016\, she was awarded a prestigious early career fellowship from the Alan Turing Institute\, UK\, for her work on logic and databases\, and before that\, she was a Postdoctoral Researcher in the Department of Computer Science of the University of Oxford. Her main research interests lie in the areas of logic\, knowledge representation and reasoning\, and neurosymbolic learning\, while her recent outcomes involve scaling symbolic reasoning to billions of triples\, as well as addressing open problems in neuro-symbolic learning. Her research has been published in top-tier machine learning\, AI\, and database venues (NeurIPS\, ICML\, SIGMOD\, VLDB\, PODS\, AAAI\, IJCAI\, etc.).
URL:https://www.etis-lab.fr/event/training-neural-models-using-logic-results-challenges-and-applications/
LOCATION:Zoom
CATEGORIES:Seminar
ORGANIZER;CN="Vassiis Christophides":MAILTO:vassilis.christophides@ensea.fr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20241015T133000
DTEND;TZID=Europe/Paris:20241015T150000
DTSTAMP:20260408T200331
CREATED:20241001T142628Z
LAST-MODIFIED:20241015T084144Z
UID:8568-1728999000-1729004400@www.etis-lab.fr
SUMMARY:Séminaire DATAAI - Minh Ha Quang
DESCRIPTION:An optimal transport and information geometric framework for Gaussian processes\nAbstract:\nInformation geometry (IG) and Optimal transport (OT) have been attracting much research attention in various fields\, in particular machine learning and statistics. In this talk\, we present results on the generalization of IG and OT distances for finite-dimensional Gaussian measures to the setting of infinite-dimensional Gaussian measures and Gaussian processes. Our focus is on the Entropic Regularization of the 2-Wasserstein distance and the generalization of the Fisher-Rao distance and related quantities. In both settings\, regularization leads to many desirable theoretical properties\, including in particular dimension-independent convergence and sample complexity. The mathematical formulation involves the interplay of IG and OT with Gaussian processes and the methodology of reproducing kernel Hilbert spaces (RKHS). All of the presented formulations admit closed form expressions that can be efficiently computed and applied practically. The mathematical formulations will be illustrated with numerical experiments on Gaussian processes. \nBio:\nMinh Ha Quang is the team leader of the Functional Analytic Learning team in the RIKEN Center for Advanced Intelligence Project (AIP)\, Tokyo\, JAPAN. He received his PhD in mathematics from Brown University (Providence\, RI\, USA) under the supervision of Stephen Smale. Before joining RIKEN\, he was a researcher at the Pattern Analysis and Computer Vision group at the Italian Institute of Technology (Istituto Italiano di Tecnologia) in Genoa (Genova)\, Italy. Prior to Italy\, he was a postdoctoral researcher at the University of Vienna\, Austria\, and the Humboldt University of Berlin\, Germany. His current research interests focus on machine learning and statistical methodologies using theories and techniques from Functional Analysis and related mathematical fields. In particular\, he has been working on theories and methods involving reproducing kernel Hilbert spaces (RKHS)\, Riemannian geometry\, Matrix and Operator Theory\, Information Geometry\, and Optimal Transport\, especially in the Infinite-Dimensional setting. \nTeams link: https://teams.microsoft.com/l/meetup-join/19%3ameeting_YjA3NjcxODItZTdjNy00Yzg0LThkYjQtNTg2MDhlYmEwMjY0%40thread.v2/0?context=%7b%22Tid%22%3a%22aa8bdaa4-8feb-46c0-b5e6-31c96337579b%22%2c%22Oid%22%3a%22c4e82db7-e9d5-4310-b5c4-91f9189f0cba%22%7d \n 
URL:https://www.etis-lab.fr/event/seminaire-dataai-minh-ha-quang/
LOCATION:ENSEA\, salle 331\, 6 avenue du Ponceau\, Cergy\, 95000\, France
CATEGORIES:ETIS,Seminar
ORGANIZER;CN="Xuan-Son Nguyen":MAILTO:xuan-son.nguyen@ensea.fr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20241010T153000
DTEND;TZID=Europe/Paris:20241010T170000
DTSTAMP:20260408T200331
CREATED:20241001T074009Z
LAST-MODIFIED:20241004T165217Z
UID:8566-1728574200-1728579600@www.etis-lab.fr
SUMMARY:Présentation "tandem" ETIS
DESCRIPTION:Sur le thème des “low-techs”\, présentation tandem\, avec Aurélien Béranger (UTC)\, et Arnaud Blanchard (ETIS). \nAurélien Béranger est doctorant en sciences de l’information et de la communication\, le titre provisoire de sa thèse est “Écologies du faire. Les discours et la matière de la hiérarchisation technologique dans le mouvement low-tech”. \nPrésentation de Aurélien Béranger\nMouvement low-tech\, communautés innovantes\, et outils numériques d’appropriation technologique \nRésumé : L’objet de cette présentation est de donner un aperçu de recherches doctorales visant à investiguer ce qui se cache sous la formule « low-tech ». Elle sera structurée en deux temps. Tout d’abord\, le concept de low-tech sera resitué dans la généalogie de la promotion de technologies alternatives et le mouvement low-tech\, tel qu’il se développe en France depuis une quinzaine d’années\, sera présenté dans toute sa diversité. Dans un second temps\, seront présentées des cas d’études de communautés de pratiques développant des technologies dites low-tech. Il s’agira\, outre de donner un aperçu sur les formes communautaires d’innovation dans le domaine matériel\, de présenter les places qui sont faites aux outils numériques dans ces espaces et comment ces derniers peuvent être développés pour répondre à des enjeux d’appropriation et de démocratisation des technologies. \n 
URL:https://www.etis-lab.fr/event/presentation-tandem-etis/
LOCATION:ENSEA\, Curium\, avenue du Ponceau\, Cergy\, 95014\, France
CATEGORIES:ETIS,Seminar
ORGANIZER;CN="Camille Simon Chane":MAILTO:camille.simon-chane@ensea.fr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20240704T110000
DTEND;TZID=Europe/Paris:20240704T123000
DTSTAMP:20260408T200331
CREATED:20240628T094357Z
LAST-MODIFIED:20240628T094449Z
UID:8411-1720090800-1720096200@www.etis-lab.fr
SUMMARY:Séminaire NEURO - Lionel Obadia
DESCRIPTION:“Do robots offer a good opportunity for ethnographic investigation?” reflections based on research in progress\nLionel Obadia (Université Lumière Lyon 2 / LARHRA) \nThe ethnography of robots is a fast-developing field of investigation\, but one with currently ill-defined boundaries: research based on direct experience of robots (in the lab / in the wild)\, observation\, analysis and reporting\, is gradually becoming established in the landscape of methodological approaches to the study of robots ‘in society’ or human-machine interactions. However\, not everything referred to as ethnography is based on exactly the same empirical approaches or contextualised theorising. Using a few examples taken from my own fieldwork\, in laboratories\, museums and socialisation spaces in France and Japan\, I will try to show the scope and limits of an anthropologically inspired ethnography\, in the case of robotic or robotised fieldwork\, possibly compared with other similar environmental ethnographies. \nLionel Obadia is a professor of social and cultural anthropology at the Université Lumière Lyon 2\, specialising in religions\, magic and witchcraft. He is the author of over 200 publications and several books\, including Bouddhisme et Occident (L’Harmattan)\, Shalom Bouddha! (Berg)\, La religion et La sorcellerie : mythes et réalités (Le Cavalier bleu)\, La marchandisation de Dieu (CNRS)\, L’anthropologie des religions et La spiritualité (La Découverte).
URL:https://www.etis-lab.fr/event/seminaire-neuro-lionel-obadia/
LOCATION:CY St-Martin\, ETIS meeting room\, avenue François-Mitterand\, Cergy\, France
CATEGORIES:ETIS,Seminar
ORGANIZER;CN="Joffrey Becker":MAILTO:joffrey.becker@ensea.fr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20240703T140000
DTEND;TZID=Europe/Paris:20240703T150000
DTSTAMP:20260408T200331
CREATED:20240628T093720Z
LAST-MODIFIED:20240628T093720Z
UID:8407-1720015200-1720018800@www.etis-lab.fr
SUMMARY:Séminaire ETIS : Stéphane Canu
DESCRIPTION:“Recherches actuelles en IA et apprentissage” / “Latest research trends in AI & ML”\nStéphane Canu\nLaboratoire LITIS EA 4108 – INSA de Rouen\, Normandie Université\, et\nAdjoint du Directeur scientifique du secteur mathématiques\, physiques\, nanosciences et STIC (en charge de l’IA)\nService de la Stratégie de la Recherche et de l’Innovation\,\nMinistère de l’Enseignement Supérieur et de la Recherche \n 
URL:https://www.etis-lab.fr/event/seminaire-etis-stephane-canu/
LOCATION:Office du tourisme de Pontoise\, Place de la Piscine\, Pontoise\, 95300\, France
CATEGORIES:ETIS,Seminar
ATTACH;FMTTYPE=image/jpeg:https://www.etis-lab.fr/wp-content/uploads/2024/06/s_canu_SJTU.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20240613T110000
DTEND;TZID=Europe/Paris:20240613T130000
DTSTAMP:20260408T200331
CREATED:20240607T073342Z
LAST-MODIFIED:20240607T073342Z
UID:8374-1718276400-1718283600@www.etis-lab.fr
SUMMARY:What will we be saying about AI in ten years’ time?
DESCRIPTION:What will we be saying about AI in ten years’ time?\nSéminaire proposé par Julia Ive\, Queen Mary University\, invitée à ETIS en juin 2024. \nDr Julia Ive is a Assistant Professor in Natural Language Processing at the School of Electronic Engineering and Computer Science at Queen Mary University of London. Together with her research team\, she is working on fairness and privacy aspects of textual data\, as well as human-AI collaboration in mental health care. She is currently leading a 3-year US-funded research project on bias in paediatric mental health. Previously\, as a Research Fellow at Imperial College London she led a UK-funded breakthrough pilot in privacy preservation of mental health text.
URL:https://www.etis-lab.fr/event/what-will-we-be-saying-about-ai-in-ten-years-time/
LOCATION:CY St-Martin\, ETIS meeting room\, avenue François-Mitterand\, Cergy\, France
CATEGORIES:ETIS,Seminar
ATTACH;FMTTYPE=image/jpeg:https://www.etis-lab.fr/wp-content/uploads/2024/06/julia_ive-scaled-e1717745609928.jpg
ORGANIZER;CN="Laura Cohen":MAILTO:laura.cohen@ensea.fr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20240606T153000
DTEND;TZID=Europe/Paris:20240606T170000
DTSTAMP:20260408T200331
CREATED:20240522T060157Z
LAST-MODIFIED:20240522T060157Z
UID:8345-1717687800-1717693200@www.etis-lab.fr
SUMMARY:Séminaire ETIS - Anna Schaeffner et Joffrey Becker
DESCRIPTION:Le laboratoire ETIS UMR 8051 a le plaisir de vous inviter à son premier séminaire Tandem. Anna Schaeffner et Joffrey Becker exploreront la souplesse sous différents aspects. \nDate: 6 juin 2024 à 15:30\nLieu: Curium de l’ENSEA\, 6 avenue du Ponceau\, Cergy\nLien zoom: https://cnrs.zoom.us/j/94434369537?pwd=NzJ5K0R6MzNXdmtQeE41WlN1K3UxZz09\nMeeting ID: 944 3436 9537\nPasscode: zXkpZ8 \nSouple\, jusqu’où ?\nNotre intervention se fera en trois temps. Dans un premier temps\, Joffrey Becker s’essaiera à une cartographie inverse de la souplesse en s’attachant à décrire diverses situations d’interaction humains-systèmes caractérisées par une grande rigidité. Cette étape permettra d’envisager différents domaines du souple\, ou différentes modalités où une réflexion sur la souplesse peut intervenir. Dans un deuxième temps\, Anna Schaeffner présentera les aspects de son travail où elle explore la notion de souplesse en design\, par et pour la pratique\, en concevant de nouvelles modalités d’interaction entre humains et objets à comportement. Son approche privilégie le travail de matériaux mous et la réalisation d’interfaces tangibles adaptatives\, et elle questionne les conditions nécessaires pour faire appel à la déformation comme moyen d’adaptation\, d’interaction autant que d’expression. Enfin\, ces deux interventions courtes seront suivies d’une discussion animée par Alexandre Pitti. \nAnna Schaeffner est designer d’interaction et chercheuse. Après avoir étudié le design produit en France\, elle a obtenu une licence (2018) et un master (2021) en design d’interaction\, à la Kunsthochschule Weissensee à Berlin où elle vit depuis 2015. Aujourd’hui\, elle est inscrite en doctorat basé sur la pratique à EnsadLab Paris\, dans le groupe d’interaction réflexive et au cluster d’excellence « matters of activity image\, space\, material » de la Humbolt Universität de Berlin. Ses recherches portent sur la robotique souple et la conception de la déformation comme vecteur de mouvement\, d’adaptation dynamique des matériaux et d’expressivité. Dans le cadre de sa pratique de conception\, elle étudie les formes hybrides d’interaction afin d’améliorer la connexion entre les objets robotiques et leurs environnements. \nJoffrey Becker est anthropologue à l’École nationale supérieure de l’électronique et de ses applications et chercheur à ETIS (UMR CNRS 8051). Ses recherches portent sur la robotique et l’intelligence artificielle\, et plus particulièrement sur les relations entre humains et machines. Elles visent à mieux saisir comment les machines dites intelligentes questionnent nos modèles sur un plan à la fois ontologique\, interactionnel et sociétal\, et ce indépendamment de leur forme. Ces travaux ont donné lieu à de nombreuses présentations publiques\, à la publication d’articles et chapitres d’ouvrages\, ainsi qu’à l’écriture d’un livre intitulé Humanoïdes\, Expérimentations croisées entre arts et sciences\, paru en 2015 aux Presses Universitaires de Paris Ouest.
URL:https://www.etis-lab.fr/event/seminaire-etis-anna-schaeffner-et-joffrey-becker/
LOCATION:ENSEA\, Curium\, avenue du Ponceau\, Cergy\, 95014\, France
CATEGORIES:ETIS,Seminar
ORGANIZER;CN="Camille Simon Chane":MAILTO:camille.simon-chane@ensea.fr
END:VEVENT
END:VCALENDAR