Allocution de bienvenue et ouverture de la journée par Monsieur de Doyen de la Faculté des Sciences Exactes et Appliquées.
Pr. KHEDDOUCI Hamamache
Dr. BOUHENNI Sarra
Dr. OUALI Abdelkader
Dr. OUALI Abdelkader
Professeur
Conseiller Scientifique - Département d'Évaluation de la Recherche
Co-Directeur de l’Ecole Doctorale InfoMaths 512http://edinfomaths.universite-lyon.fr/
Pr. Kheddouci Hamamache is a professor of computer science at Lyon 1 University and a member of the LIRIS laboratory. His research focuses on graphs, distributed systems, and data exploration. As a visiting professor at several international universities, he regularly collaborates with renowned institutions such as the University of New South Wales (UNSW) in Sydney and the University of Illinois in Chicago.
https://perso.univ-lyon1.fr/hamamache.kheddouci
Maître de conférences
Coordinator of the track Data Science for Master of Computer Science. University of Caen.
Dr. Ouali Abdelkader is working on new approaches to carry Data Mining (DM) tasks such as clustering, pattern mining or pattern sampling under constraints, where a user can use additional knowledge to guide the search process. This field requires the development of hybrid methods ranging from Operation Research (OR), Constraints Programming (CP), and dedicated DM methods.
https://ouali193.users.greyc.fr
PhD
Phd, LIRIS Lab. UMR CNRS 5205.
Researcher-engineer in real-time ML.
Dr Bouhenni Sarra focuses on developing fast, efficient, and scalable algorithms for large graphs and Big Data. Her PhD in data science involved designing distributed algorithms for graph pattern matching on Think-Like-A-Vertex graph processing systems. Her core skills include Spark and Scala.
https://sarra-bouhenni.github.io/index/
The recent advances in data acquisition and production have led to the generation of very large volumes of (complex) data. Indeed, conventional systems are not able to respond to the issues related to the storage, exploration and analysis of Big Data. Graphs are powerful models that can capture different relationships between data, give them a better representation and facilitate their exploration. However, the graphs obtained from these large datasets are usually too large and heterogenous. Their exploration requires new and effective tools. This brings new research issues.
In this talk, we will discuss some real graph data locks and their equivalent issues in graph theory. We will present some theoretical results on graphs that could contribute to solve big data and cybersecurity issues.
In line with recent advancements in the field of graphs and distributed systems, this workshop provides practical insights into distributed graph processing approaches, equipping participants with skills in handling massive graph data using Apache Spark's GraphX API. GraphX enables the distributed processing of large graphs by leveraging Spark’s scalable, fault-tolerant processing capabilities, making it an ideal choice for graph-based computations like graph pattern matching.
The workshop will cover essential concepts of distributed graph processing, hands-on exercises with Spark and GraphX, and an overview of different distributed programming models like vertex-centric and edge-centric paradigms. By the end of the session, participants will have a solid foundation in implementing scalable graph algorithms, preparing them to tackle real-world challenges in large-scale graph processing
L’extraction de motifs à partir de données numériques constitue une étape essentielle en fouille de données, visant à identifier des relations implicites au sein de grands volumes de données. Ces relations peuvent être interprétées par des experts ou exploitées dans d'autres tâches.
Au cours de cette présentation, je décrirai des méthodes basées sur la programmation par contraintes pour l'extraction des motifs d'intervalles fermés, ainsi que des stratégies d'échantillonnage
Le Laboratoire d'Informatique et des Technologies de l'Information d'Oran (LITIO) ambitionne de créer une enceinte au sein de l'université d'Oran1 pour développer des thématiques d'actualité en informatique et ses applications. Ce personnel d'enseignants/chercheurs est actif en matière de recherche, de publications, de communications et de projets. Notre ambition est d'assurer convenablement la formation doctorale et puis de développer des activités avec l'industrie.
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Enseignants-Chercheurs de l'université Oran 1 Ahmed Ben Bella :
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