Wajdi Dhifli
Associate Professor (Maître de conférences) at the University of Lille
Adjunct Professor (Professeur Associé) at the University of Quebec At Montréal
Contact: wajdidhifli{at}gmail{dot}com /wajdi{dot}dhifli{at}univ-lille{dot}fr
Address: 3, rue du Professeur Laguesse BP83 - 59006 - Lille Cedex, France.
I joined the University of Lille since September 1st 2017 as an associate professor (maître de conférences) in computer science. I worked previously as a postdoctoral research associate with the I3-bionet team at the Institute of Systems and Synthetic Biology (iSSB) - University of Évry-Val-d'Essonne, also as a postdoctoral research associate with the bioinformatics lab at the University of Quebec At Montreal (UQAM), and as a research engineer at LIMOS - University Clermont Auvergne. I received a PhD in Computer Science from University Clermont Auvergne in December 2013.
My research interests include theoretical and applied research in machine learning, big data analytics and bioinformatics with a particular interest in graph data and applications in bio- and health informatics.
Our paper on « Learning Global-Local Multi-Scale Node Embeddings with Random Walks and Landmark-Guided Optimization » has been accepted in CIKM, 2025.
Our paper on « Modélisation par mélange de Gaussiennes pour améliorer la diversité d’un modèle génératif VAE-GAN » has been accepted in BDA, 2025.
Our paper on « A Genetic and Graph-Guided Feature Learning Strategy for Improving Decision Tree Construction » has been accepted in Cluster Computing, Springer, 2025.
Our paper on « A coregulatory influence map of glioblastoma heterogeneity and plasticity – From cells in vitro to tumors and back again » has been accepted for publication in Nature Peer Journal Precision Oncology 2025!
Our paper « Optimizing MLP Network Structure for Classification Problems Using PSO and Dominating Vertex Set » has been accepted in IEEE ICDM workshops, 2024.
Our preprint on « A coregulatory influence map of glioblastoma heterogeneity and plasticity – From cells in vitro to tumors and back again » is out on biorxiv. Check it out!
Our preprint on « A Genetic and Graph-Guided Feature Learning Strategy for Improving Decision Tree Construction » is on HAL. Check it out!
Our paper « Optimisation par PSO avec utilisation du dominating vertex set pour le paramétrage des couches cachées d'un MLP » has been accepted in EGC 2024.
Our paper « Accuracy and Diversity-Aware Multi-Objective Approach for Random Forest Construction » has been accepted for publication in Expert Systems with Applications, Elsevier, 2023!
Our paper « From SIR to SEAIRD: a novel data-driven modeling approach based on the Grey System Theory to predict the dynamics of COVID-19 » has been accepted for publication in Applied Intelligence, Springer, 2022!
Our paper « Instance Matching in Knowledge Graphs through Random Walks and Semantics » has been accepted for publication in Future Generation Computer Systems, Elsevier, 2021!
Our paper « An Overlapping Clustering Approach for Precision, Diversity and Novelty-Aware Recommendations » has been accepted for publication in Expert Systems with Applications, Elsevier, 2021!
Our paper « Instance Matching in Knowledge Graphs Through Dynamic, Distributed and Affinity-Preserving Random Walk » has been accepted for publication in IEEE BigData, 2020!
Our paper « Optimisation Collective d’Arbres de Décision dans une Forêt Aléatoire » has been accepted for publication in BDA, 2020!
Our paper « Data Linking Over RDF Knowledge Graphs: A Survey » has been accepted for publication in the journal Concurrency and Computation: Practice and Experience, Wiley, 2020!
Our paper « Evolutionary Mining of Skyline Clusters of Attributed Graph Data » in Information Sciences, Elsevier, 2020 is out!
Our paper « BIGMat: A Distributed Affinity-Preserving Random Walk Strategy for Instance Matching on Knowledge Graphs » has been accepted for publication in IEEE BigData, 2019!
Our paper « Context-Aware Instance Matching Through Graph Embedding in Lexical Semantic Space » has been accepted for publication in Knowledge-Based Systems, Elsevier, 2019!
I'm co-chairing the ICML 2019 Workshop on Computational Biology (WCB) @ ICML 2019 Join us for another exciting workshop!
I joined the program committee of the workshop Advances in managing and mining large evolving graphs@ECML-PKDD 2019
Our paper « A Data Sampling and Attribute Selection Strategy for Improving Decision Tree Construction » has been accepted for publication in Expert Systems with Applications, Elsevier, 2019!
Our paper « Context-Aware Instance Matching Through Graph Embedding in Lexical Semantic Space » has been accepted at the 32nd International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE), 2019!
Our paper « Latent network-based representations for large-scale gene expression data analysis » has been accepted for publication in BMC Bioinformatics, BMC, 2019!
11/2010-12/2013: Ph.D in Computer Science from University Clermont Auvergne (France)
Topic: Topological and Domain Knowledge-based Subgraph Mining: Application on Protein 3D-Structures. (Thesis manuscript) (Examiners report)
Distinction: Very Honorable (highest distinction)
Funding: PhD Grant From The Ministry of Higher Education and Research, France
Committee Members: Prof. Mohammed Javeed Zaki (Rensselaer Polytechnic Institute, USA), Prof. Abdoulaye Baniré Diallo (University of Quebec At Montreal, Canada), DR. Jan Ramon (Katholieke Universiteit Leuven, Belgium), DR. Jean-François Gibrat (INRA, Jouy-en-Josas, France), DR. David W. Ritchie (INRIA, Nancy, France), DR. Jean Sallantin (LIRMM, Montpellier, France), Prof. Annegret Wagler (LIMOS, Clermont-Ferrand, France), Prof. Engelbert Mephu Nguifo (LIMOS, Clermont-Ferrand, France)(Advisor)