Plenary Lectures
and tutorials
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Plenary Lectures
AHMED-CHAWKI CHAOUCHE
Nowadays, computers have so expanded as they are spreading everywhere in the environment, they will become invisible and they disappear in everyday objects. This vision led to several new computer domains, such as mobile computing, ubiquitous computing, and ambient intelligence.
The main aim of such systems is to integrate tiny microelectronic processors and sensors into everyday objects in order to make them smart. These connected objects are heterogeneous, context-aware, interconnected, and often mobile evolving in an open and a dynamic environment.
From prevention to pro-active assistance of persons during their daily activities, like Ambient Assisted Living technologies, the ambient systems provide a support for safety and comfort, improving the life quality of persons.
From a forward-looking viewpoint, ambient intelligence appears to be one of the major issues for the years ahead. The ubiquity of connected objects in everyday life is made possible thanks to the miniaturization and performance of electronic components, the wide dissemination of mobile and wireless networks, and the control of production costs. Therefore, ambient intelligence is destined to become a key pillar of the economy.
Abstract:
Ahmed-Chawki Chaouche has received his PhD in computer science from both university of Pierre and Marie Curie, Paris 6 in France and university of Abdelhamid Mehri, Constantine 2 in Algeria (2015). Currently, he is an associated professor in Constantine 2 university, he is also a permanent researcher in computer science at MISC laboratory. Actually, he is the head of e-learning platform of Constantine 2 university and he is a member of Innovation and Incubation Unit (IIU) in charge of monitoring projects. His research interests include ambient intelligence modelling, multi-agent systems, and implementation of smart and connected objects incorporating planning and machine-learning approaches.
About the Lecturer:
Lecture 2: Social Commerce: Research and Applications
Mohamed Gharzouli
Social Networking Services (SNS) is one of the major innovations that have transformed e-commerce in recent years. In addition, there is a growing awareness of the convergence between social networks and e-commerce.
This phenomenon is better known as "social commerce or s-commerce". In this context and according to statistics published by Statista in 2017, in the period 2016-2019, business sales on social networks are predicted to generate more than 3 billion USD in revenue worldwide.
Despite the development and rapid evolution of s-commerce in recent years, many issues surrounding this concept are not yet fully clear. The goal of this keynote is to expose a state of the art on s-commerce and to discuss the different research areas in this field.
Abstract:
Mohamed Gharzouli is an Associate Professor in the Faculty of New Technologies of Information and Communication, University of Abdelhamid Mehri –Constantine 2, Algeria. He was born in Constantine (Algeria). He received his BS degree in Computer Science from Mentouri University of Constantine in 2002 and Magister degree in Computer Science from Larbi Tebessi University of Tebessa (Algeria) in 2004. He has completed his PhD degree in Advanced Information systems from Mentouri University in September 2011. He received his habilitation qualifications (Accreditation to supervise research) from Abdelhamid Mehri University in 2015. His researches interests include service-oriented architectures, Web applications, and use of information technologies in different fields like Business and Education.
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About the Lecturer:
Lecture 3: Statistical data science and some unsupervised learning problems
Faicel Chamroukhi
Statistics and machine learning are foundational to data science, and the unsupervised learning of useful information, from heterogeneous and unlabeled raw data, is one of the most popular and challenging problems in statistical data science. This is becoming of broader interest in the today's statistics & data science community, in particular with the increasing prevalence of large-scale (big) data. I this talk, I will introduce some statistical latent data models, and unsupervised algorithms, that are able to discern knowledge from raw data, while addressing problems regarding the data complexity, including heterogeneity, high dimensionality, dynamical behaviour, and missing information. I will focus on new methods that allow to discover useful information through advanced model-based clustering techniques, or to make predictions of future data, via flexible statistical classification techniques. Some of the presented questions are connected to the ongoing research projects AStERiCs and ANR SMILES, which aim at introducing an unsupervised learning framework and scaled inference algorithms for transforming large-scale data, into knowledge.
Abstract:
Faicel Chamroukhi (https://chamroukhi.com) is Professor of Statistics and Data Science at University of Caen, department of Mathematics and Computer Science, and the Lab of Mathematics Nicolas Oresme (LMNO), UMR CNRS 6139, since September, 2016. From 2011 to 2015, he've been Associate Professor of Computer Science & Machine Learning at University of Toulon, department of computer science, and the Information Sciences and Systems Lab (LSIS), UMR CNRS 7296. In 2015-2016, he was awarded a CNRS research leave, at the Lab of Mathematics Paul Painlevé, UMR CNRS 8524, in Lille. He defended his Accreditation to Supervise Research/Habilitation à Diriger les Recherches, in applied mathematics and computer science, at Toulon University, in December 2015. He defended his Ph.D. thesis, in the same area, at Compiègne University of Technology, Heudiasyc UMR CNRS 7253 and IFSTTAR labs, in December 2010; He obtained his Master degree, in June 2007, from PARIS 6 (Pierre & Marie Curie) University. His primary research interests include statistical modeling and inference, unsupervised learning, in large-scale scenarios.
About the Lecturer:
