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!

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

Publications

Proceedings and editorials
  • [P1] W. Inoubli, S. Aridhi J.A. Fernandes de Macêdo, E. Mephu Nguifo and K. Zeitouni. Proceedings of the Workshop on Advances in managing and mining large evolving graphs (LEG) co-located with The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2020), Ghent Belgium, 14-18 September 2020.
Paper in journals with reviewing committee
  • [J6] B.Marwa, C. Katar, W.Inoubli. Large-scale knowledge graph representation learning. Knowledge and Information Systems, (2024). [IF = 2.7].
  • [J5] SMH. Mirsadeghi, H.Bahsi, R.Vaarandi, W.Inoubli. Learning From Few Cyber-Attacks: Addressing the Class Imbalance Problem in Machine Learning-Based Intrusion Detection in Software-Defined Networking. IEEE Access 11: 140428-140442 (2023). [IF = 3.9].
  • [J4] W. Inoubli, S. Aridhi, H. Mezni, M. Maddouri, E. Mephu Nguifo. A Distributed and Incremental Algorithm for Large-Scale Graph Clustering. Future Generation Computer Systems, Elsevier, 2022. [IF = 7.187].
  • [J3] A. Mouakhera, W. Inoubli, C. Ounoughib, A. Koa. Expect: EXplainable Prediction model for Energy ConsumpTion. Mathematics, 2022, [IF = 2.258]
  • [J2] S. Bouasker, W. Inoubli, S. Ben Yahia and G. Diallo. Pregnancy Associated Breast Cancer gene expressions : new insights on their regulation based on Rare Correlated Patterns. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2020 [IF = 3.015]
  • [J1] W. Inoubli , S. Aridhi, H. Mezni, M. Maddouri, E. M. Nguifo. An Experimental Survey on Big Data Frameworks. Future Generation Computer Systems, Elsevier, 86, pp. 546-564, 2018. [IF = 5.768]
International conferences/workshops with program committee
  • [IC9] K. Abidi, W. Inoubli and E.M Nguifo DGCN: Learning Graph Representations Via Dense Connections. 27th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, 2023, Athens, Greece.
  • [IC8] K. Ammar, W. Inoubli , S. Zghal and E.M Nguifo Trans-Trip: Translation-based embedding with Triplets for Heterogeneous Graphs. 27th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, 2023, Athens, Greece.
  • [IC7] K. Ammar, W. Inoubli , S. Zghal and E.M Nguifo Graph Representation Learning for Recommendation Systems: A short review. 6th International Conference on Information and Knowledge Systems (ICIKS), 22nd to the 23rd of June, 2023, Portsmouth, UK.
  • [IC6] H .Mirsadeghi,H. Bahsi, W. Inoubli Deep Learning-based Detection of Cyberattacks in Sofware-Defined Networks. 13th EAI International Conference on Digital Forensics & Cyber Crime, November 16-18, 2022, Boston, United States.
  • [IC5] W. Inoubli , A. Brun DGL4C: a Deep Semi-supervised Graph Representation Learning Model for Resume Classification. 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 .
  • [IC4] M. Shahin, W. Inoubli, S. Attique Shah, S. Ben Yahia and D. Draheim. Distributed Scalable Association Rule Mining Over Covid-19 Data. International Conference on Future Data and Security Engineering (FDSE), Virtual Mode, November 24-26, 2021.
  • [IC3] W. Inoubli , S. Aridhi, H. Mezni, M. Maddouri and E. Mephu Nguifo. A Comparative Study on Streaming Frameworks for Big Data . Proceedings of the Latin America Data Science Workshop co-located with 44th International Conference on Very Large Data Bases (VLDB 2018), Rio de Janeiro, Brazil, Aug 27, 2018.
  • [IC2] W. Inoubli ,S. Aridhi, H. Mezni, M. Maddouri and E. Mephu Nguifo. An Experimental Survey on Big Data Frameworks. Extremely Large Databases Conference (XLDB) 2017, Clermont Ferrand, France. (Lightning talk, poster)
  • [IC1] W. Inoubli , L. Almada, T.L. Coelho da Silva, G. Coutinho, L. Peres, R.P. Magalhaes, J.F. de Macedo, S. Aridhi, E. Mephu Nguifo. A Distributed Framework for Large-Scale Time-Dependent Graph Analysis. Joint Workshop on Large-Scale Evolving Networks and Graphs in conjunction with ECML-PKDD 2017, Skopje, Macedonia.
National conferences with program committee
  • [NC3] W. Inoubli, A. Brun. Un algorithme d'apprentissage profond et semi-supervisé basé sur la représentation de graphes pour la classification des CV. Extraction et Gestion des Connaissances (EGC 2024), Dijon, France.
  • [NC2] W. Inoubli, S. Aridhi, H. Mezni, M. Maddouri, E. M. Nguifo. Un algorithme distribué pour le clustering de grands graphes. Extraction et Gestion des Connaissances (EGC 2020), Bruxelles, Belgique.
  • [NC1] W. Inoubli, S. Aridhi, H. Mezni, M. Maddouri, E. M. Nguifo. An Experimental Survey on Big Data Frameworks. 34-èmes journées de la conférence « Gestion de Données – Principes, Technologies et Applications » (BDA 2018), Bucarest, Romania.

Student supervision

PhD students
  • Dorssaf Sellami, since December 2023, co-advising (40%) with Sabeur Aridhi and Riadh farah "Scalable Knowledge Graph Representation Learning for Drugs Repositioning"
  • Chaima Khemiri, since December 2022, co-advising (50%) with Mohamed Fareh "Deep Graph Metric Learning for Remote Sensing Image Classification and Retrieval"
  • Khouloud Ammar, since Mars 2021, co-advising (50%) with Engelbert Mephu Nguifo, Sami Zghal and Amel Borgi "Dynamic heterogeneous graph representation learning",
Master students
  • Marwa Badrouni, 2022/2023, co-advising (50%) with Cheker Katar "Large Scale Knowledge Graph Representation Learning",
  • Khairi Abidi, 2021/2022, co-advising (50%) with Engelbert Mephu Nguifo "Learning Graph Representation Via Dense Connections",

CURRICULUM VITAE

Education

Experience

Teaching

Since September 2023, University of Artois, France
2022 – 2023, TELECOM Nancy, University of Lorraine, France
2020 – 2021, Faculty of science of Tunis, University of Tunis EL-Manar, Tunisia
2019 – 2020, IDMC, University of Lorraine, France
2017 – 2019, University of Jendouba, Tunisia

contact

wissem dot inoubli at univ dash artois dot fr
CRIL, University of Artois
CRIL Lab, Faculty of Science, Office 352
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