Habib Hamam

Research professor, Research director in EMAT laboratory, University of Moncton
Canada

Title:

Dissemination of scientific research results: trends, threats and prospects

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Abstract:

Currently we are experiencing a boom in publications and graduations. Rapid and abundant open access publications by gigantic publishers, such as Hindawi, MDPI and SAGE, require deep thought. Scientific integrity is in question. On top of that comes the adoption by universities, and employers in general, of biometric criteria, such as the H-index which is affected by these abundant publications, will shape the future of research and development in a way that is not necessarily reasonable. A researcher who strives to explore new concepts or directions to produce pioneering results to fill knowledge gaps needed to develop new policies, standards, products, services, technologies or new and innovative processes, this researcher can no longer compete with researchers who incessantly publish very incremental results. The future of our graduates and young researchers will depend on the future decisions of stakeholders in relation to these aspects. Hence, a moment of reflection is needed. This conference will discuss all these aspects, try to predict future trends and propose solutions. Artificial intelligence will be taken as an example..

Biography:

Professor Habib Hamam (Senior Member, IEEE) received the B.Eng. and M.Sc. degrees in information processing from the Technical University of Munich, Germany, in 1988 and 1992, respectively, the Ph.D. degree in physics and applications in telecommunications from the University of Rennes I conjointly with France Telecom Graduate School, France, in 1995, and the Postdoctoral Diploma degree “Accreditation to Supervise Research in Signal Processing and Telecommunications” from the University of Rennes I, in 2004. From 2006 to 2016, he was a Canada Research Chair holder in “Optics in Information and Communication Technologies,” for a period of ten years. He is currently a Full Professor with the Department of Electrical Engineering, University of Moncton. His research interests include optical telecommunications, wireless communications, diffraction, fiber components, RFID, information processing, data protection, COVID-19, and deep learning. He is a Senior Member of OSA, and a Registered Professional Engineer in New-Brunswick. He is among others Editor-in-Chief of CIT-Review and an Associate Editor of the IEEE Canadian Review..

Mehrez Zribi

CESBIO
France

Title:

Contribution of satellite observation for monitoring water and carbon cycles in the context of climate change

Abstract:

In the context of the strong climatic and anthropogenic changes undergone by the Earth, the scientific activity is very rich to allow a precise and continuous monitoring of the various climate variables. This involves an essential modeling component to establish scenarios for the future and also a strong observation dynamic. For a long time, this observation has been particularly ensured by numerous in situ measurement networks. For several years, Earth observation has become an essential tool for spatio-temporal monitoring. The contribution of space is very important to have a global vision of the evolutions and to ensure the analysis of the climatic anomalies. This concerns the water and carbon cycles, with variables on continental surfaces, ocean surfaces and the atmosphere. The proposed presentation aims to give an overview of this rich space activity and its evolution in recent years..

Biography:

M. Zribi is a Director of Research in CNRS (French National Scientific Research Center) and the Head of CESBIO (Centre d’Etudes Spatiales de la BIOsphère). In 1995, he joined the Centre d’Etude des Environnements Terrestre et Planétaires Laboratory [Institut Pierre Simon Laplace/CNRS], Vélizy, France. In 2001, he joined CNRS organism to develop microwave remote sensing research applied to land surface. Since October 2008, he has been with the Centre d’Etudes Spatiales de la Biosphère, Toulouse. During the period (2008-2012), he was with the French Institute of Research for Developement to develop researches in water resources based on remote sensing in semi-arid regions. He is expert on microwave remote sensing applied to land surfaces. Mehrez Zribi has published actively in refereed journals with high impact factor (150 papers). He coordinated publication of 20 books about remote sensing for land surfaces. His H index (Web of Science) is equal to 48. He coordinated and participated to several research projects funded by different research programs (CNES, ANR, ESA, FP5, FP6, FP7 etc). He is associated editor for three international journals (Geophysical instrumentation, Methods and data systems (EGU), Nature/Scientific Reports and Remote Sensing/MDPI). He is senior member of IEEE Geoscience and Remote Sensing.

Habib Benali

Scientific Director, PERFORM Centre and Professor, Department of Electrical and Computer Engineering Faculty of Engineering and Computer Science Concordia University Montreal, QC,
Canada

Title:

Virtual brain activity and predictive physiopathology

Abstract:

The objective of our research program in Biomedical Imaging and Healthy Aging is to better understand brain activity in healthy aging and to shed light on factors predicting conversion to neurodegenerative disease. Indeed, understanding neuronal activity, brain metabolism and patho-physiological process will enable the development of innovative mathematical models by combining biological and biomedical images from the basic modelling of the brain's anatomo-functional circuits to models of tau protein accumulation. In such “virtual brain activity and pathology” environment, the outcome of brain disease development for individual subjects can be foreseen by simulations. Numerical simulation tools would allow prediction of the progress of the disease as well as an understanding of its causes, which remain uncertain. This numerical approach is a new paradigm of the study of the patho-physiological process in healthy aging of subjects at-risk for neurodegenerative disease. This approach, referred to as “predictive physiopathology”, offer better health through prevention..

Biography:

Habib Benali completed my PhD in Applied Mathematics and Statistics at Rennes University in 1985. He joined the French National Institute of Health and Medical Research (INSERM) in 1989. He served as Head of the Laboratory of Functional Imaging (INSERM U678 unit with over 65 members) from 2008 to 2013 and Deputy Director of the Biomedical Imaging Laboratory (with over 100 members), INSERM - The National Center for Scientific Research (CNRS) and Sorbonne University until 2015. Together with Prof. Julien Doyon, from the Université de Montréal (UdeM), he founded and became co-director of the International Laboratory of Neuroimaging and Modelisation of the INSERM-Sorbonne University and UdeM administrative bodies in 2007. He is a regular research member of the Centre de Recherche Mathématiques of UdeM since 2002 and a researcher at Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal, UdeM, since 2005. He is currently the Scientific Director for the PERFORM Centre, NSERC Canada Research Chair Tier 1 in Biomedical Imaging and Healthy Aging and Professor at the Faculty of Engineering and Computer Science at Concordia University. In the last 30 years, he has gone from starting a new neuroimaging research activity to directing a productive laboratory in France a nd Canada with activities that span from the development of new mathematical modeling and image analysis techniques to cognitive neuroscience and clinical applications. During this productive time in his scientific career, he published more than 300 peer reviewed papers in the best scientific journals. He is a member of national and international per review committees, executive committees and member of Advisory Board & committees.

Bhiksha RAMAKRISHNAN

Carnegie Mellon University, Pittsburgh,
PA, United States

Title:

Privacy and Security Issues in Speech Processing

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Abstract:

As the use of speech as a modality of interacting with devices becomes more popular, a natural question arises -- can these systems be trusted? In addition to the many usual requirements of trustworthiness such as accuracy, reliability, fairness, security, etc., speech systems face unique challenges relating to privacy. Speech carries a lot more information than the mere content of what was spoken -- it also carries information about the speakers themselves, including their gender, nationality and native language, emotional state, health, and a variety of other biometric and demographic information. In the process of using the speech service, users expose themselves to unintended exploitation of this information. The privacy risks associated with the use of speech based interaces is now increasingly recognized by governments and corporate institutions alike. In this talk we will discuss the privacy-related challenges of the use of speech as a biometric signal, and the need for protection. We will discuss the legal landscape of the problem, and introduce the various solutions that have been proposed, including cryptographic, multi-party-computation based, and hashing-based solutions, and their limitations. Finally, time permitting we will briefly also discuss more recent methods based on adversarial processing of speech, and how these solutions may in fact serendipitously address some of the other aspects of trustworthiness of speech-processing.

Biography:

Dr. Bhiksha Raj is a tenured (full) professor of Computer Science at Carnegie Mellon University. Dr. Raj completed his Ph.D in Electrical engineering and Computer Science from Carnegie Mellon University, USA, in 2000. He was at Compaq (Cambridge) Research Lab until 2001. From 2001 to 2008 he led Speech Research at Mitsubishi Electric Research Labs. Since 2008 he has been a full-time faculty at Carnegie Mellon. Over his career Dr. Raj has made pioneering contributions to three broad areas of research: Speech and Audio Processing, Privacy and Security in Multimedia Processing, and lately, Deep Learning and AI. He holds over 30 patents in these areas, is co-editor of three technical books and has published over over 360 research papers in peer-reviewed journals and conferences. His current research spans topics of high contemporary importance, such as exploiting data and structure redundancy for deep learning and AI systems, preserving user privacy in speech and audio processing systems, learning and evaluating classifiers under real-world labeling assumptions, and robustness of AI systems to adversarial attacks. He is a fellow of the IEEE. .

Gérard CHOLLET

Télécom-SudParis (SAMOVAR),
France

Title:

Self-Supervised Speech Processing

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Abstract:

Most speech processing applications require a large set of labeled data to train their models. The labelling process is costly, prone to errors and time consuming. The question is: Is it possible to make use of non-labeled data to facilitate the training process? Additionally, is there a way to train a powerful feature embedding that can benefit the down-stream fine-tuning and multi-task training? Self-Supervised Learning (SSL) appears to answer the questions. Quoting Yann LeCun, who originally proposed this approach in 2019: “In Self-Supervised Learning, the system learns to predict part of its input from other parts of its input“. This principle has been successfully applied to text processing and computer vision. This presentation will focus on the recent developments of the same principle for speech applications. Self-supervised speech representation learning is closely related to acoustic word embedding and learning with NO lexical resources. The obtained vectorial embeddings can then be used for a variety of applications such as recognition, synthesis, speaker verification, emotion detection, etc. With its powerful expressive and adaptive ability, self-supervised models have brought revolutionary improvements on the performance on almost all these speech tasks.

Biography:

Pr. Gérard Chollet studied Linguistics, Electrical Engineering and Computer Science at the University of California, Santa Barbara where he was granted a PhD in Computer Science and Linguistics. He taught at Memphis State University and University of Florida before joining CNRS. In 1981, he was asked to take in charge the speech research group of Alcatel. In 1983, he joined a newly created CNRS research unit at ENST (Telecom-ParisTech within Institut Mines-Telecom). In 1992, he was asked to participate to the development of IDIAP, a new research laboratory of the `Fondation Dalle Molle' in Martigny, Switzerland. From 1996 to 2012, he was back full time at ENST, managing research projects and supervising doctoral work. He supervised more than forty doctoral thesis. CNRS decided in July 2012 to grant him an emeritus status. He visited the Boise State University in 2013 and the University of Eastern Finland in 2014. He is now VP of Research at Intelligent Voice. His main research interests are in phonetics, automatic audio-visual speech processing, speech dialog systems, multimedia, pattern recognition, biometrics, privacy-preserving digital signal processing, speech pathology and speech training aids. His main publications are available from his Google Scholar Citations profile..