Keynote Speakers of ICEDL 2024

Prof. Olivier Rioul
Télécom Paris, Institut Polytechnique de Paris, France

Olivier Rioul (https://perso.telecom-paristech.fr/rioul/) is full Professor at the Department of Communication and Electronics at Télécom Paris, Institut Polytechnique de Paris, France. He graduated from École Polytechnique and from École Nationale Supérieure des Télécommunications, Paris, France, where he obtained his PhD degree. His research interests are in applied mathematics and include various, sometimes unconventional, applications of information theory such as inequalities in statistics, hardware security, and experimental psychology. He has been teaching information theory and statistics at various universities for twenty years and has published a textbook which has become a classical French reference in the field.

Prof. Toufik Bakir
University of Burgundy, France

Toufik Bakir received his Ph.D. degree in industrial automatics from the University of Claude Bernard-Lyon I, Lyon, France, in 2006. He was an associate professor at the Le2i (Laboratory of electronics, computer science and image) at the University of Burgundy (2007-2020). He became a full professor since 2021 at ImViA (Image and Artificial Vision laboratory) of the University of Burgundy. He is the head of the computer science and electronics department since 2020. His research interests include dynamic systems (industrial processes, biomedical systems) in terms of modeling, optimization and control.

Assoc. Prof. Ismail BENNIS
University of Haute Alsace, France

Ismail Bennis earned in 2009 a bachelor’s degree in mathematics and computer science from the Université Mohammed V in Rabat, Morocco. 2011, he received a master’s degree in Computer Networks and Telecommunications from the same university. He completed his PhD in 2015 under joint supervision between the Université Mohamed V in Rabat, Morocco and the Université de Reims Champagne-Ardenne in France. From 2015 to 2017, he worked as a temporary professor for research and teaching (A.T.E.R) at the University of Reims. Between 2017 and 2020, he worked as an associate professor at La Rochelle University. His research interests include routing protocols with quality of service over wireless sensor networks, IoT and outlier detection. Since September 2020, he has worked as an associate professor at the University of Haute Alsace.

Speech Title: Outlier Detection Techniques in IoT: challenges and recent approaches

Wireless Sensor Networks (WSNs), and more generally, the Internet of Things (IoT), are widely used to gather information and monitor the environment in various applications, such as medical, agricultural, manufacturing, and military. The goal is to transmit data from sensors to the base station. However, this data is susceptible to outliers, which can occur due to the sensor nodes themselves or the harsh environment in which they are deployed. Therefore, WSNs must detect outliers and take action to ensure data Quality of Service (QoS) in terms of reliability and accuracy, as well as prevent further degradation of application efficiency. This need has resulted in many research efforts to propose efficient outlier detection and classification solutions and improve the performance of existing ones. The challenge is detecting outliers and classifying them as errors to be ignored or important events requiring further action. This talk will discuss enhanced and effective outlier detection and classification approaches for WSNs. The enhancement tackles the clustering, outlier detection, and classification phases.