Guest speakers

Professor Kamel SMAILI

LORIA LAB, University of Lorraine

The Future of Low-Resource NLP: Investigating Advanced Neural Network Architectures Utilizing META Models

Professor Adel BELOUCHRANI

Professor Adel Belouchrani, IEEE Fellow, ENP.

Algerian Academy of Science and Technology

Signal Separation: From Model Driven Approaches to Data Driven Approaches

Prof Kamel Smaïli is a Professor of Computer Science at the University of Lorraine, where he specializes in natural language processing. He conducts his research within LORIA, a laboratory affiliated with the University of Lorraine. His career began with a degree in Computer Engineering from USTHB University in Algiers, Algeria, in 1986, followed by a Ph.D. from Henri Poincaré University in 1991, and a Habilitation à diriger la recherche (HDR) from the University of Nancy 2 in 2001. Between 1999 and 2001, he was seconded to CNRS. In 2013, Kamel Smaïli founded the SMarT research team (https://smart.LORIA.fr/) at LORIA, focusing on natural language processing using statistical and neural approaches, as well as developing deep learning methods for textual and numerical data.With a strong commitment to mentoring young researchers, he has supervised 19 doctoral students, 18 of whom have already defended their theses, with two more about to do so.Kamel Smaïli has evaluated several research projects for ANR, ANRT, and international projects, such as NeuroInsight 2022.From 2015 to 2022, he played a leading role in international cooperation by co-directing a CNRS-associated international laboratory (LIA) called DataNet, involving two laboratories from the University of Lorraine and several Moroccan universities, including UIR.Kamel Smaïli's research has led to the publication of over 150 articles in international journals and conferences. He remains actively engaged in research as the coordinator of the national ANR project (TRADEF) and the European Chist-Era Access Multilingual Information opinions (AMIS) project, completed in 2019.Kamel Smaïli is also highly active in the international academic community, having organized and chaired major international conferences such as ICNLSSP 2017 and ICALP 2019, and serving on several program committees of world-renowned conferences, including ICASSP, Interspeech, and LREC, among others.His academic reputation has led to invitations to give lectures in various countries, including Japan, France, Spain, Poland, Algeria, Tunisia, and Morocco. Additionally, he has participated as a jury member in over 80 thesis and HDR (Habilitation to Direct Research) defenses in France, Germany, Spain, India, Ireland, Algeria, Morocco, and Tunisia.

Abstract

In this presentation, I will talk about the issues of under-resourced languages and more especially those concerning Arabic dialectes. These vernacular languages vary depending on the area where they are spoken and they have the particularity to evolve quickly in terms of vocabulaires since they do not obey strictly to a linguistic paradigm. Furthermore, the processing becomes harder when the data are extracted from social networks. Then one of the potential possibility to handle these vernacular languages is probably the use of the existing amount of audios and encode them in order that they could be mapped into the same close space as the corresponding texts and then create in such a way new resources and new data for these not well covered languages. We will present one of the solution proposed by META for this issue based on SeamlessM4T and NLLB.

Adel Belouchrani was born in Algiers, Algeria, on May 5, 1967. He received the State Engineering degree from Ecole Nationale Polytechnique (ENP), Algiers in 1991, an MSc degree in signal processing from the Institut National Polytechnique de Grenoble, France in 1992, and his PhD in signal and image processing from Télécom Paris, France in 1995. He was a postdoctoral fellow at the Electrical Engineering and Computer Sciences Department, University of California at Berkeley, CA, USA, from 1995 to 1996 and was with the

Department of Electrical and Computer Engineering, Villanova University, Villanova, PA, USA, as a research associate, from 1996 to 1997. From 1998 to 2005, he was with the Electrical Engineering Department, ENP, as an associate professor. Since 2006, he has been a full professor with ENP. His research interests are in statistical signal processing, (blind) array signal processing, time-frequency analysis, and time-frequency array signal processing with applications in biomedical and communications. Dr. Belouchrani is a founding member of the Algerian Academy of Science and Technology. Dr. Belouchrani was awarded an Arab-American Frontiers Fellowship of the U.S. National Academy of Sciences, Engineering and Medicine to conduct research on the blind identification of power sources in processors design at Brown University, Rhode Island, USA in 2016. He has served as Associate Editor of the IEEE Transactions on Signal Processing for two terms from 2013 to 2017 and as Editorial board member of the Digital signal processing Journal (Ed. Elsevier) from 2011 to 2019. He has been Senior Area Editor of the IEEE Transactions on Signal Processing for two terms from 2017 to 2021 and an elected member of the EURASIP Special Area Team (SAT)- Theoretical and Methodological Trends in Signal Processing for the 2018-2020 term, as well as an elected member of the IEEE Sensor Array and Multichannel Technical Committee for 2019-2021 term. Prof. Adel Belouchrani has been named a 2020 IEEE Fellow.

Abstract

Blind signal separation is a mature field of research with a broad range of applications. It is motivated by practical problems that involve several source signals and several sensors. Each sensor receives a mixture of the source signals. The problem under consideration consists of recovering the original waveforms of the source signals without any knowledge of the mixture structure. The latter may be instantaneous linear mixture, convolutive mixture or nonlinear mixture. This talk concentrates on Model driven approaches with some applications in various fields of engineering. A discussion on Data driven approaches versus Model driven ones will be provided.

Dr. Nadia ZENATI

Director of research at the Centre for Development of Advanced Technologies-CDTA, Algiers.

Réalité virtuelle et interaction 3D: innovations et applications en santé

Dr. Nadia Zenati-Henda is director of research at the Centre for Development of Advanced Technologies-CDTA in Algiers. She is currently a researcher at the Robotics and Industrial Automation Division. She heads the Human machine Interaction, Virtual and Augmented Reality research group (IRVA team). She received her PhD degree in Computer Science from the University of Franche-Comté (France) in 2008. She is author/co-author of around a hundred of scientific publications (including conferences and journals) and participated to several research projects. Her current research focuses on how Virtual and Augmented Reality can provide new solutions in healthcare area such as functional rehabilitation and medical training.

Abstract

L'omniprésence de la réalité virtuelle et de la réalité augmentée sur les ordinateurs sous toutes leurs formes (PC, tablettes, smartphones, etc.) et la popularisation des capteurs nécessitent le développement de nouvelles modalités d'interface et d'interaction homme-machine.

Le développement de nouvelles méthodes d'interface et d'interaction homme-machine (IHM) est devenu nécessaire en raison de l'omniprésence de la réalité virtuelle et de la réalité augmentée sur divers périphériques (PC, tablettes, smartphones, etc.). Ceci est rendu possible par de nouveaux outils pour l'interaction gestuelle ou vocale, et pour la prise en compte des émotions, des intentions ou du contexte social.

La modélisation des IHM est devenue un défi majeur avec l'apparition des technologies de réalité virtuelle et augmentée, car de nombreux problèmes restent à résoudre, tels que l'analyse du comportement humain, la prise en compte de la conscience de l'utilisateur, l'évolution dans un contexte critique, le partage des tâches ou le co-tasking dans un environnement collaboratif.

L’interaction 3D reste la composante motrice de la réalité virtuelle. Elle permet à l’homme d’être un acteur capable de changer le cours des évènements dans un environnement synthétique et ainsi d’interagir avec des entités virtuelles.

L'objet de cette présentation est de donner un aperçu de ces concepts et de leurs avancées dans les domaines de la santé et de l'industrie.

La première partie sera consacrée au concept des technologies immersives et leurs implications en santé ainsi que le formalisme de l’interaction 3D collaborative.

La seconde partie de la présentation portera sur les activités de l'équipe Interaction Homme Système Réalité virtuelle & Augmentée –IRVA- du CDTA et sa contribution dans la recherche et le développement.

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