Wissem Inoubli
Associate Professor
I am an Associate Professor of Computer Science at the University of Artois and a member of the Centre de Recherche en Informatique de Lens (CRIL). Previously, I worked as a postdoctoral researcher at the Lorraine Laboratory of Research in Computer Science and its Applications (LORIA) in the BIRD team. Prior to that, I held a postdoctoral research position at Tallinn University in the Data Science Group. My research focuses on big graph analysis and explainable artificial intelligence (XIA). I earned my Ph.D. in computer science from the Faculty of Science of Tunis, University Tunis EL-Manar, Tunisia in 2021. My Ph.D. thesis was conducted in collaboration between the Faculty of Sciences of Tunis, the LORIA at the University of Lorraine, Nancy, and LIMOS at the University of Clermont Auvergne, Clermont-Ferrand. In this thesis, my primary focus was on massive data analysis (big data), complex data (big graphs), and large-scale machine learning.
Research areas
My research areas are include (but are not limited to):- Graph processing
- Graph representation learning
- Deep graph Learning
- Explainable artificial intelligence
- Big data
last news!
April 2024 Ph.D. Thesis on Deep Graph Representation Learning on non-uniform 3D objects more details
Febrary 2024 I joined the program committee of the 27th European Conference on Artificial Intelligence ECAI 19-24 October 2024
November 2023, Our paper Un algorithme d'apprentissage profond et semi-supervisé basé sur la représentation de graphes pour la classification des CV has been accepted at 24th Francophone Conference on Knowledge Extraction and Management, EGC 2024 Dijon
May 2023, Our paper Trans-Trip: Translation-based embedding with Triplets for Heterogeneous Graphs has been accepted at 27th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, 6-8 September 2023, Athens Greece
May 2023, Our paper DGCN: Learning Graph Representations Via Dense Connections has been accepted at 27th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, 6-8 September, 2023, Athens Greece
April 2023, Our paper Graph Representation Learning for Recommendation Systems: A short review has been accepted at 6th International Conference on Information and Knowledge Systems, 22nd to the 23rd of June, 2023, Portsmouth, UK
August 2022, Our paper DGL4C: a Deep Semi-supervised Graph Representation Learning Model for Resume Classification has been accepted at RecSys in HR'22: The 2nd Workshop on Recommender Systems for Human Resources, in conjunction with the 16th ACM Conference on Recommender Systems, September 18--23, 2022, Seattle, USA.
April 2022, Our paper A Distributed and Incremental Algorithm for Large-Scale Graph Clustering has been accepted for publication in Future Generation Computer Systems (IF = 7.187).
October 2021, Our paper Distributed Scalable Association Rule Mining Over Covid-19 Data has been accepted at the International Conference on Future Data and Security Engineering (FDSE)
October 2021, I'joined the montors committee of the DATA-DRIVEN ENERGY EFFICIENCY DEEPHACK
Hackathon
April 2021, I'joined the organization committee of the 10th International Conference on Model and Data Engineering, 21-23 June 2021, Tallinn, Estonia
January 2021, I successfully defended my PhD thesis on Analysis and Mining of Large Dynamic Graphs: case of graph clustering
Committee: Lotfi Ben Romdhane, Osmar Zaiane, Anis Yazidi, Mohamed Mohssen Gamoudi, Sabeur Aridhi, Amel Borgi, Engelbert Mephu Nguifo.
presentation
