Main research topics

Data mining & Machine learning

Large scale learning & Big Data

Bioinformatics & health-informatics

Publications

Preprints 

1. T.K. Saha, M. Ouzzani, H. Hammady, A.K. Elmagarmid, W. Dhifli, M. Al Hasan. A Large Scale Study of SVM-Based Methods for Abstract Screening in Systematic Reviews.

Book Chapters

1. W. Dhifli, E. M. Nguifo. Motif Discovery in Protein 3D-Structures Using Graph Mining Techniques. In: Pattern Recognition in Computational Molecular Biology: Techniques and Approaches, Wiley Book Series on Bioinformatics: Computational Techniques and Engineering, 2015.(DOI: 10.1002/9781119078845.ch10)

Journals

1. N.E.I. Karabadji, A. Amara Korba, A. Assi, H. Seridi, M. Aimen, Y.Ghamri-Doudane, A. Lakhdari, M. Elati, W. Dhifli. A Genetic and Graph-Guided Feature Learning Strategy for Improving Decision Tree Construction. Cluster Computing (Springer), 2025 (accepted). [IF=4.1]

2. C. Bernhard, K. Geles, G. Pawlak, W. Dhifli, A. Dispot, J. Dusol, M. Kondratova, S. Martin, M. Messé, D. Reita, D. Tulasne, I. Van Seuningen, N. Entz-Werle , S. A. Ciafrè, M. Dontenwill, M Elati . A coregulatory influence map of glioblastoma heterogeneity and plasticity – From cells in vitro to tumors and back again. npj Precision Oncology, 2025. (DOI: 10.1038/s41698-025-00890-0) [IF=8.0]

3. N.E.I. Karabadji, A. A. Korba, A. Assi, H. Seridi, S. Aridhi, W. Dhifli. Accuracy and Diversity-Aware Multi-Objective Approach for Random Forest Construction. Expert Systems With Applications (Elsevier) 225:120138, 2023. (DOI: 10.1016/j.eswa.2023.120138) [IF=7.5]

4. K. M. Pékpé, D. Zitouni, G. Gasso, W. Dhifli, B.C. Guinhouya. From SIR to SEAIRD: a novel data-driven modeling approach based on the Grey System Theory to predict the dynamics of COVID-19. Applied Intelligence (Springer) 1-10, 2022 (DOI: 10.1007/s10489-021-02379-2). [IF=3.5]

5. A. Assi, W. Dhifli. Instance Matching in Knowledge Graphs through Random Walks and Semantics. Future Generation Computer Systems (Elsevier) 123:73-84, 2021. (DOI: 10.1016/j.future.2021.04.015) [IF=6.1]

6. C.E. Berbague, N.E.I. Karabadji, H. Seridi, P. Symeonidis, Y. Manolopoulos, W. Dhifli. An Overlapping Clustering Approach for Precision, Diversity and Novelty-Aware Recommendations. Expert Systems With Applications (Elsevier) 177:114917, 2021. (DOI: 10.1016/j.eswa.2021.114917) [IF=7.5]

7. W. Dhifli, N.E.I. Karabadji, M. Elati. Evolutionary Mining of Skyline Clusters of Attributed Graph Data. Information Sciences (Elsevier) 509:501-514, 2020. (DOI: 10.1016/j.ins.2018.09.053) [IF=6.8] 

8. A. Assi, H. Mcheick, W. Dhifli. Data Linking Over RDF Knowledge Graphs: A Survey. Concurrency and Computation: Practice and Experience (Wiley) 32(19):e5746, 2020. (DOI: 10.1002/cpe.5746) [IF=1.5]

9. A. Assi, H. Mcheick, A. Karawash, W. Dhifli. Context-Aware Instance Matching Through Graph Embedding in Lexical Semantic Space.  Knowledge-Based Systems (Elsevier) 186:104925, 2019. (DOI: 10.1016/j.knosys.2019.104925) [IF=7.6]

10. N.E.I. Karabadji, I. Khelf, H. Seridi, S. Aridhi, D. Remond, W. Dhifli. A Data Sampling and Attribute Selection Strategy for Improving Decision Tree Construction. Expert Systems With Applications (Elsevier) 129:84-96, 2019 (DOI: 10.1016/j.eswa.2019.03.052). [IF=7.5]

11. T. K. Saha, A. Katebi, W. Dhifli, M. Al Hassan. Discovery of Functional Motifs from the Interface Region of Oligomeric Proteins using Frequent Subgraph Mining. IEEE/ACM Transactions on Computational Biology and Bioinformatics 16(5): 1537 - 1549, 2019 (DOI: 10.1109/TCBB.2017.2756879). [IF=3.4]

12. W. Dhifli, Julia Puig, Aurélien Dispot, M. Elati. Latent network-based representations for large-scale gene expression data analysis. BMC Bioinformatics 19(13):466, 2019. (DOI: 10.1186/s12859-018-2481-y) [IF=3.3]

13. R. Saidi, W. Dhifli, M. Maddouri, E. M. Nguifo. Efficiently mining recurrent substructures from protein 3D-structure graphs. Journal of Computational Biology (JCB)(Mary Ann Liebert, Inc.) 26(6):561–571, 2019. (DOI: 10.1089/cmb.2018.0171) [IF=1.7]

14. N.E.I. Karabadji, S. Beldjoudi, H. Seridi, S. Aridhi, W. Dhifli. Improving Memory Based User Collaborative Filtering  with Evolutionary Multi-Objective Optimization. Expert Systems With Applications (Elsevier) 98:153–165, 2018 (DOI: 10.1016/j.eswa.2018.01.015). [IF=7.5]

15. W. Dhifli, S. Aridhi, E. M. Nguifo. MR-SimLab: Scalable Subgraph Selection with Label Similarity for Big Data. Information Systems (Elsevier) 69:155–163, 2017.  (DOI: 10.1016/j.is.2017.05.006) [IF=3.4]

16. N.E.I. Karabadji, H. Seridi, F. Bousetouane, W. Dhifli, S. Aridhi. An Evolutionary Scheme for Decision Tree Construction.  Knowledge-Based Systems (Elsevier) 119:166-177, 2017. (DOI: 10.1016/j.knosys.2016.12.011) [IF=7.6]

17. W. Dhifli, A. B. Diallo. ProtNN: Fast and Accurate Protein 3D-Structure Classification in Structural and Topological Space. BMC BioData Mining 9 (1): 1-17, 2016. (DOI: 10.1186/s13040-016-0108-2) [IF=6.1]

18. W. Dhifli, R. Saidi, E. M. Nguifo. Smoothing 3D protein structure motifs through graph mining and amino-acids similarities. Journal of Computational Biology (JCB) 21 (2): 162-172, 2014. (DOI: 10.1089/cmb.2013.0092) [IF=1.7]

Conferences and Workshops

1. A. Assi, N.E.I. Karabadji, M. Elati, W. Dhifli. Learning Global-Local Multi-Scale Node Embeddings with Random Walks and Landmark-Guided Optimization. The 34th Conference on Information and Knowledge Management (CIKM): (accepted), Seoul, South Korea, 2025.

2. N. Manaa, N.E.I. Karabadji, H. Seridi, M. S. M. Mendjel, I. Hadjadji, W. Dhifli. Modélisation par mélange de Gaussiennes pour améliorer la diversité d’un modèle génératif VAE-GAN. 41ème Conférence sur la Gestion de Données – Principes, Technologies et Applications (BDA): (accepted), Toulouse, France, 2025.

3. N.E.I. Karabadji, H. Seridi, A. A. Korba, S. Aridhi, W. Dhifli. Optimizing MLP Network Structure for Classification Problems using PSO and Dominating Vertex Set. EDMML: 4th Workshop on Evolutionary Data Mining and Machine Learning @ ICDM: page 529-534, Abu Dhabi, UAE, 2024.

4. I. Hadjadji, N.E.I. Karabadji, H. Seridi, N. Manaa, W. Dhifli. Optimisation par PSO avec utilisation du dominating vertex set pour le paramétrage des couches cachées d'un MLP. The 24ème conférence francophone sur l'Extraction et la Gestion des Connaissances (EGC): pages 349-350, Dijon, France, 2024.

5. G. Pawlak, J. Puig, A. Dispot, W. Dhifli, M. Elati. BLCA-RegMap portal: a co-regulatory influence network view of bladder cancer heterogeneity. 25th international bladder cancer network, Barcelona, Spain, 2022.

6. A. Assi, M. Elati, W. Dhifli. Instance Matching in Knowledge Graphs Through Dynamic, Distributed and Affinity-Preserving Random Walk. IEEE International Conference on Big Data (IEEE BigData): pages 892-897, Los Angeles, CA, USA, 2020.

7. N.E.I. Karabadji, H. Seridi, A. A. Korba, S. Aridhi, W. Dhifli. Optimisation Collective d’Arbres de Décision dans une Forêt Aléatoire. 36ème Conférence sur la Gestion de Données – Principes, Technologies et Applications (BDA): pages 42-43, Paris, France, 2020.

8. A. Assi, H. Mcheick, W. Dhifli. BIGMat: A Distributed Affinity-Preserving Random Walk Strategy for Instance Matching on Knowledge Graphs. IEEE International Conference on Big Data (IEEE BigData): pages 1028-1033, Los Angeles, CA, USA, 2019. 

9. A. Assi, H. Mcheick, W. Dhifli. Context-Aware Instance Matching Through Graph Embedding in Lexical Semantic Space. The 32nd International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE): pages 422-433, Graz, Austria, 2019.

10. J. Puig, A. Dispot, W. Dhifli and M. Elati. Cell-intrinsic core-regulatory circuits driving tumor-related phenotypes with the I3-OncoNet cycle. AdvCompBio2019, Barcelona, Spain, 2019.

11. W. Dhifli, Julia Puig, Aurélien Dispot, M. Elati. Latent network-based representations for large-scale gene expression data analysis. The 17th International Conference on Bioinformatics (InCOB), New Delhi, India  2018.

12. R. Saidi, W. Dhifli, M. Maddouri, E. M. Nguifo. Efficiently mining recurrent substructures from protein 3D-structure graphs. Joint ICML and IJCAI 2018 Workshop on Computational Biology (WCB), Stockholmsmässan, Stockholm, Sweden 2018.

13. W. Dhifli, N. O. Da Costa, M. Elati. An Evolutionary Schema for Mining Skyline Clusters of Attributed Graph Data. IEEE Congress on Evolutionary Computation (CEC): pages 2102-2109, Donostia - San Sebastián, Spain 2017.

14. W. Dhifli, A. B. Diallo. Face Recognition in the Wild. 20th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES): pages 1571-1580, York, UK 2016.

15. W. Dhifli, A. B. Diallo. Toward an Efficient Multi-class Classification in an Open Universe. 12th International Conference on Machine Learning and Data Mining (MLDM), New York City, NY, USA 2016 (Best paper award).

16. W. Dhifli, M. Moussaoui, R. Saidi, E. M. Nguifo. Mining Topological Representative Substructures from Molecular Networks. 13th International Workshop on Data Mining in Bioinformatics (BioKDD@ACM SIGKDD), New York City, NY, USA 2014.

17. W. Dhifli, M. Moussaoui, R. Saidi, E. M. Nguifo. Towards an Efficient Discovery of Topological Representative Subgraphs. Le dix-neuvième congrès national sur la Reconnaissance de Formes et l’Intelligence Artificielle (RFIA), Rouen, France 2014.

18. W. Dhifli, R. Saidi, E. M. Nguifo. Smoothing 3D protein structure motifs through graph mining and amino-acids similarities. Journées Ouvertes en Biologie, Informatique et Mathématiques (JOBIM): pages 65-74 , Toulouse, France 2013.

19. W. Dhifli, R. Saidi, E. M. Nguifo. A novel approach for mining representative spatial motifs of proteins. ACM Conference on Bioinformatics, Computational Biology and Biomedicine (ACM BCB): pages 506-508, Orlando, Florida, USA 2012.

20. W. Dhifli, R. Saidi, E. M. Nguifo. Mining representative subgraphs by substitution matrices: an application on protein structures. Machine Learning in Computational Biology (MLCB@NIPS workshops), South Lake Tahoe, Nevada, USA 2012.

21. R. Saidi, W. Dhifli, M. Maddouri, E. M. Nguifo. A novel approach of spatial motif extraction to classify protein structures. Journées Ouvertes en Biologie, Informatique et Mathématiques (JOBIM): pages 159-166, Rennes, France 2012.

22. W. Dhifli, R. Saidi, E. M. Nguifo. Frequent subgraph summarization by substitution matrices. Journées Ouvertes en Biologie, Informatique et Mathématiques (JOBIM): pages 341-342, Rennes, France 2012.

23. R. Saidi, W. Dhifli, S. Aridhi, M. Agier, G. Bronnier, D. Debroas, L. d’Orazio, F. Enault, S. Guillaume, E. M. Nguifo. Protein classification in the case of large and many-class datasets: A comparison with BLAST and BLAT. Journées Ouvertes en Biologie, Informatique et Mathématiques (JOBIM): pages 221-222, Paris, France 2011.

24. W. Dhifli, R. Saidi, J. Akaichi, E. M. Nguifo. Protein sequence classification: a comparative study of HMM classifier. Société Francophone de Classification (SFC): pages 29-32, Orléans, France 2011.

25. W. Dhifli, R. Saidi. Protein graph repository. Extraction et la Gestion des Connaissances (EGC): pages 641-642, Hammamet, Tunisia 2010.

Posters

1.  W. Dhifli, M. Mohamed, R. Saidi, E. M. Nguifo. Optimisation par PSO avec utilisation du Dominating Vertex Set pour le paramétrage des couches cachées d’un MLP. Topological Methods for Machine Learning (ICML Workshop), Beijin, China 2014.

2. W. Dhifli, M. Mohamed, R. Saidi, E. M. Nguifo. Towards an Efficient Discovery of Topological Representative Subgraphs. Topological Methods for Machine Learning (ICML Workshop), Beijin, China 2014.

3. R. Saidi, W. Dhifli, M. Maddouri, E. M. Nguifo. A novel approach of spatial motif extraction to classify protein structures. International conference on System and Molecular Biology (ISMB), California, USA 2012

4. W. Dhifli, R. Saidi, J. Akaichi, E. M. Nguifo. A comparative study of HMM classifier on protein sequence classification. ISCB Student Council Symposium meeting, at ISMB. Vienna, Autriche 2011. Poster