Wajdi Dhifli
Associate Professor (Maître de conférences) at the University of Lille
ONCOLille - CRCLille | Team DISCO (Digital systems and computational cancer)
Head of the Master 2 "Digital Systems in Healthcare" (Conception de dispositifs numériques en santé)
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'm an associate professor (maître de conférences) in computer science at the University of Lille (UFR3S) and member of the DISCO team (DIgital Systems and COmputational cancer) at CRC Lille (previously Canther) - part of the “Interdisciplinary Cancer Research Institute of Lille” ONCOLille. 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 AI, machine learning, big data analytics and bioinformatics with a particular interest in graph data and applications in cancer research.
Our paper « A universal molecular map of bladder cancer: from cell lines in vitro to tumors and back using co-regulatory networks » is out in The Journal of Urology, American Urological Association, 2026!
Our paper « Improved VAE-GAN via Mixture of Gaussians applied to Brain Tumor MRI Classification » has been accepted for publication in Knowledge-Based Systems, Elsevier, 2026!
Our paper « A universal molecular map of bladder cancer: from cell lines in vitro to tumors and back using co-regulatory networks » is out in European Urology, Elsevier, 2026!
our paper « Apprentissage Multi-Échelle Global-Local de Représentations de Nœuds par Marches Aléatoires et Optimisation Guidée par Points de Repère » has been accepted at the 29e Conférence Nationale en Intelligence Artificielle (CNIA), 2026!
Our paper « Multi-Group Overlapping Weighted Random Forests » has been accepted for publication in ICT Express, Elsevier, 2026!
Our paper « Towards Better Random Forests with Tree Weighting, Accuracy and Diversity-Preserving Pruning » has been accepted for publication in Expert Systems with Applications, Elsevier, 2026!
Our paper « Reasoning vs. Critic-Based Verification for Biomedical Relation Extraction with Large Language Models » has been accepted for publication in The third international PromptEng Workshop at the ACM WebConf'26 (WWW'26), 2026!
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 « 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 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 « 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. Engelbert Mephu Nguifo (Advisor)(LIMOS, Clermont-Ferrand, France), 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).