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!
Juin 2025, Our paper I was invited to give a talk on graph representation learning at the National Conference on Computational Intelligence and Applications 2025 (NCCIA 2025), organized by Jashore University of Science and Technology (JUST). The presentation focused on current opportunities, major challenges, and the state of the art in the field.
May 2025, Our paper WeightedHGE: Weighted Heterogeneous Graph Embedding has been accepted at 29th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, 10-12 September 2025, Osaka, Japan
May 2025, Our paper Deep Contrastive Graph Learning Framework for Hyperspectral Image Classification has been accepted at 29th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, 10-12 September 2025, Osaka, Japan
April 2025 I’m co-chairing the first edition of the International workshop on Leveraging Large Language Models and AI for Intelligent Healthcare Systems (HealthLLM) Doha, Qatar, 19-22 October, 2025
Febrary 2025 I joined the program committee of the 28th European Conference on Artificial Intelligence ECAI 25-30 October 2025
December 2024, Our paper Knowledge graph representation learning: a comprehensive and experimental overview has been accepted for publication in Computer Science Review
December 2024 We are editing a special issue of Supercomputing journal on Scalable and Deep Graph Learning and Mining
. Please submit your paper here
October 2024, Our paper Empirical Analysis of Knowledge Graph Representation Learning Techniques has been accepted at the 13th International Conference on Complex Networks and their Applications, COMPLEXNETWORKS 2024,Istanbul, Turkey
October 2024, Our paper Incorporating Multi-Scale Temporal Dynamics into Graph-Based Recommender Systems has been accepted at the 13th International Conference on Complex Networks and their Applications, COMPLEXNETWORKS 2024,Istanbul, Turkey
October 2024, Our paper Leveraging Large Language Models (LLMs) to Match Job Offers with Candidate CVs has been accepted at the 16th International Conference on Management of Digital EcoSystems, MEDES 2024,Naples, Italy
Mai 2024 I had the pleasure to give an invited talk entitled "The Power of Graph Structure in Artificial
Intelligence: Real-World Applications and Insights" at the Scientific Discovery in the light of Artificial Intelligence Day Organized by AI4U Research Unit
April 2024 I’m co-chairing the first edition of the International workshop on Scalable and Deep Graph Learning and Mining in conjunction with IEEE BIGDATA 2024
April 2024 Our paper Large Scale Knowledge Graph Representation Learning has been accepted for publication in Knowledge and Information Systems
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.
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