Biography

Zaineb CHELLY DAGDIA is an Associate Professor at Versailles Saint-Quentin-en-Yvelines University (UVSQ), Faculty of Sciences, Paris-Saclay, and a member of the Ambient Data Access and Mining (ADAM) group at the DAVID laboratory. She earned her Ph.D. in Computer Science from the University of Tunis (ISG-Campus), Tunisia, in 2014, and her HDR (qualification for supervising research) from the University of Paris-Saclay, France. Her research interests span various aspects of Artificial Intelligence, including Machine Learning, Evolutionary Algorithms, Artificial Immune Systems, scalable machine learning, approximated reasoning, granular computation, and privacy preservation. She focuses on real-world applications, particularly in the medical field and cyber-security. She has supervised five Ph.D. students (one of whom has defended), a postdoctoral researcher, a software engineer, and several master’s students. Her career includes over 50 journal papers (SCI indexed), refereed and ranked conference proceedings papers, a book, and book chapters. Her research is funded by European Union’s research and innovation programs, national grants, multi-partner projects, and bilateral research collaboration programs. She regularly serves as a Program Committee member for international conferences in her research fields and as a reviewer for several refereed international journals. She has (co-)organized and (co-)chaired several national and international conferences and workshops. She has received numerous awards, including the Young Researcher First Price (IEEE EHB’2013), the ACM-W Award, the Marie Skłodowska Curie Individual European Fellowship and the Best Reviewer Award (iCDEc 2018). She also acts as a Marie Sklodowska Curie Ambassador, selected as a Female Scientist Role Model, and selected to be among the Heidelberg-Laureate-Forum (HLF) most qualified young researchers, and among the 30 MSC talented researchers to communicate her research at the Falling Walls Labs 2018 organized by the European Commission (EC). She was also involved in several EC dissemination activities.

Google Site : [link]

Contact

zaineb dot chelly-dagdia at uvsq dot fr

zaineb dot garcia at uvsq dot fr

• Knowledge Discovery in Databases (KDD) using Computational Intelligence
• (Big) data pre-processing (feature selection)
• Big data, scalability, and distributed processing
• Approximated reasoning and granular computation
• Machine learning
• Artificial Immune Systems and Evolutionary Algorithms
• Privacy preservation (federated learning)
• Deep learning and explainability
• KDD applications for knowledge extraction (e.g., medical field, cyber-security)

• IHU Prometheus (2023-2033): PRecisiOn MedicinE for healTHcare associatEd and commUnity acquired Sepsis. Instituts Hospitalo-Universitaires (IHU), Work package co-leader.
• i-RECORDS (2022-2025): International – Rapid rEcognition of CORticosteroiDs sensitivity or resistance in Sepsis. ERA PerMed (European Research Area Network on Personalised Medicine), Work package co-leader.
• RHU RECORDS (2020-2025): Rapid rEcognition of CS sensitive or resistant Sepsis. RHU (Research Hospital University), Work package co-leader
• FHU SEPSIS (2020-2025): Saclay and Paris Seine Nord Endeavour to PersonnaliSe Interventions for Sepsis. FHU (Fédération Hospitalo-Universitaire), Work package co-leader.

Past projects

• MASTER (2018-2023): Multiple ASpects TrajEctoRy management and analysis. H2020-MSCARISE-2017, Experienced Researcher.
• RoSTBiDFramework (2017-2019): Optimised Framework based on Rough Set Theory for Big Data Pre-processing in Certain and Imprecise Contexts. H2020-MSCA-IF-2015, MSCA fellow (beneficiary).
• BIG-SKYEARTH (2015-2019): Big Data Era in Sky and Earth Observation. COST Action, Experienced Researcher.
• MUSES (2012-2015): Multiplatform Usable Endpoint Security. FP7-ICT-2011.1.4, Early Stage Researcher.

List of all publications: Google Scholar

List of the most recent publications (below):

I have obtained the following honours and awards:

• Marie Sklodowska Curie Fellowship (2015), MSCA certificate (2019)
• Best Reviewer Award (iCDEc 2018)
• ACM-Women in Computing grant (2014)
• IEEE Young Researcher, First Price (EHB 2013)

I have been honoured to:

• Be invited as an evaluator for the Information and Communications Technology (ICT) proposals within the European Commission (Big Data proposals)
• Act as a Marie Sklodowska Curie ambassador
• Be named as a female scientist role model
• Be a panellist at the Parlamentarium for the debate: « Education, Research & Innovation: developing concrete synergies », Brussels, Belgium
• Selected to be part of the Marie Skłodowska-Curie Actions-Falling Walls Lab
• Selected to be part of the Marie Skłodowska-Curie Researchers’ Night Event
• Selected to be among the Heidelberg-Laureate-Forum most qualified young researchers to meet the Abel-Prize, Fields-Medal, the ACM-Turing award, the Nevanlinna Prize and the ACM Prize in Computing winners
•  Selected to organize a workshop with Prof Stephen Smale (Fields Medal)

Invited talks

• 10/09/2023: “Federated Learning: Hype or Hope?”, 21th International Conference of Complex Acute Illness, 2023 – scientific session: “Quantitative understanding of critical illness: Integrating Mechanism and Machine Learning”, Augsburg, Germany
• 4-5/05/2023: “Unleashing the Power of AI: Revolutionizing Industries and Personalizing Healthcare”, Tunisian Women and DATA + AI Summit 2023, Tunis, Tunisia. The event is organized by the RECONNECTT association in France in partnership with Women in Data Science at Stanford University (WiDS).
• 08/09/2022: “Federated learning for healthcare”, 20th International Conference of Complex Acute Illness, 2022
• 10/2022: “Effects of COVID-19 pandemic on education and society”, Inspire Health Summit 2022
• 21/07/2022: “Seeking the fortification of the convergence between biological computation and computational biology”, Dynamics of Immune Repertoires: Exploration and Translation, workshop, Dresden, Germany  
• 17 – 18/05/2018: `A success story’, All Wales Summer School 2018, Cardiff, Wales, UK
• 05 – 06/07/2017: `A success story’, All Wales Summer School 2017, Swansea, Wales, UK
• 06/02/2017: `My MSC fellowship: The story so far’, MSCA Campaign – From the Association to Participation, Tunis, Tunisia.
• 09 – 11/09/2015: `Data pre-processing based on Rough Sets and the link to other theories’, The International Afro-European Conference for Industrial Advancement, Villejuif, France. 

Editorial activities

• Guest Editor
  • Engineering Applications of Artificial Intelligence, Special Issue on Recent Advances in Immune Computation 
  • Applied Soft Computing — Special Issue on Recent Advances in Immune Computation
• Associate Editor
  • • Applied Computing and Intelligence
• Regular Program Committee Member for various international conferences and several refereed international journals  

Organization of scientific events

• The 2024 International Joint Conference on Rough Sets (IJCRS 2024), Rough Set School and Tutorial  (co-organizer and chair)
• FedCSIS/RSTA 2024, FedCSIS/RSTA 2023, FedCSIS/RSTA 2022– International Symposium on Rough Sets: Theory and Applications (co-organizer and chair)
• Workshop on Federated Learning, 10/01/2023, Paris-Saclay, France (co-organizer and chair)
• EEE CEC 2021, IEEE CEC 2020, IEEE CEC 2019, IEEE CEC 2018 – Special Session on Artificial Immune Systems – IEEE World Congress on Computational Intelligence (co-organizer)
• The first international Metaheuristics Summer School – MESS 2018, Taormina, Italy (Publicity chair)
• Workshop on Algorithms in Nature (Organizer, Mentored by Prof Stephen Small (Fields Medal awardee)), Heidelberg Laureate Forum, Germany (2017)
• `Neural Networks and Fuzzy Logic’ session at `The Int’l Conf. on Swarm Intelligence’, Harbin, China (chair) (2013)

Expertise and responsibilities

• Board member of EGC (Association Internationale Francophone d’Extraction et de Gestion des Connaissances (EGC)).
• Co-responsable for EGC school (e-EGC).
• Board member of the Tunisian Artificial Intelligence Society
• Advisory Board Member for the European Researchers’ Night (Tunisia 2018)
• Evaluator for ANRT: Evaluator of a CIFRE (Industrial Agreements for Training through Research) research project submitted to ANRT (National Association for Research and Technology) (2023).
• Invited evaluator (2019), by the European Commission, to assess H2020-ICT projects.

PhDs (current)

Gwenolé Abgrall

• Thesis title: Fluid responsiveness assessment using AI –assisted medical waveforms analysis. 
• Doctoral school: Innovation thérapeutique : du fondamental à l’appliqué (ITFA), Paris-Saclay University.
• Funding: Société de Réanimation de Langue Française (SRLF).
• Supervisors: Z. Chelly Dagdia, X. Monnet, K. Zeitouni.
• Defense: 2026

Rahma HELLALI

• Thesis title: Machine learning based approaches for multi-omics data in personalized treatment of sepsis.
• Doctoral school: Sciences et Technologies de l’Information et de la Communication (STIC), Paris-Saclay University.
• Funding: RECORDS project. 
• Supervisors: Z. Chelly Dagdia (thesis diretcor), K. Zeitouni.
• Defense: 2025

Saloua BOUABBA

• Thesis title: A federated learning approach for privacy of semantically enriched mobility data.
• Doctoral school: Sciences et Technologies de l’Information et de la Communication (STIC), Paris-Saclay University.
• Funding: LabEx Digicosme & Ecole supérieure d’informatique, électronique, automatique (ESIEA).
• Supervisors: Z. Chelly Dagdia, K. Zeitouni, N. Agoulmine,  B. Haidar.
• Defense: 2025

Kodjo Mawuena M Amekoe

• Thesis title: Machine Adaptive Learning applied to Fraud.
• Doctoral school: Sciences, Technologies, Santé – Galilée, Sorbonne Paris North University.
• Funding: CIFRE (BPCE).
• Supervisors: Z. Chelly Dagdia, H. Azzag, M. Lebbah
• Defense: 2025

PhDs (defended)

Manel Jerbi

• Thesis title: Android Malware Detection based on Real and Artificial Patterns using Evolutionary and Rough Set Approaches.
• Defense: 27/12/2021
• Supervisors: Z. Chelly Dagdia, S. Bechikh
• Jury members: Nahla BEN AMOR, Nadia ESSOUSSI, Chih-Cheng HUNG, Lamjed BEN SAID, 
• Doctoral school: Computer Science, ISG-Tunis, Tunisia
• Funding: No funding.

Postdoc

Hassan Moustafa Harb

• Period: 01/2022 – 12/2022
• Laboratory/Group: DAVID/ADAM
• Supervisors: Z. Chelly Dagdia, K. Zeitouni.
• Funding: RECORDS project

Software Engineer

Ahmad Ktaish

• Period: 2020- 2021
• Laboratory/Group: DAVID/ADAM
• Supervisors: Z. Chelly Dagdia, K. Zeitouni.
• Funding: RECORDS project

MSc (current)

Malek Adouani

• MS title: Sepsis Clinical Data Enrichment: Secure and Unbiased Augmentation via Generative AI Techniques.
• Funding: DAVID, UVSQ, Paris-Saclay 
• Supervisors: Z. Chelly Dagdia, K. Zeitouni.
• Defense: 12/2024

MSc (defended)

Khaled Sethom

• MS title: Evolutionary Induction of Regression Trees for Predictive Analytics.
• Defense: 20/12/2021
• Supervisors: Z. Chelly Dagdia, S. Bechikh.
• University: FSEGN, Tunisia. 

Omar Ben Amor

• MS title: Many-Objective Optimization of Wireless Sensor Network Deployment
• Defense: 16/04/2019
• Supervisors: Z. Chelly Dagdia, S. Bechikh.
• University: ISG-Tunis, Tunisia. 

Kaouther Ben Ali

• MS title: A New Version of the Dendritic Cell Immune Algorithm based on the K-Nearest Neighbors
• Defense: 16/06/2015
• Supervisors: Z. Chelly Dagdia, Z. Elouedi.
• University: ISG-Tunis, Tunisia. 

• Since 2023, I am the coordinator for the teaching unit « Foundations of Computer Science I  » for 1st year of the Bachelor’s program at UVSQ, Paris Saclay [~14 groups].
• Since 2021, I have been the coordinator for the teaching unit « Data Mining » for the Master 2 DataScale program, Paris Saclay.
• Member of the Selection Committee – « Maître de conférences » position (GALAXIE) – University Evry, Paris-Saclay.
• Served as a member of the PhD admission commission – sciences and technologies of information and communication (STIC) Doctorial school, Paris-Saclay. (2023)
• Jury member of the “Doctoral students prize from the Saclay plateau”, Paris Saclay, France (2022, 2023)
• Co-responsible for the renewal of the DAVID laboratory website. Since March 2022, I have been collaborating with two members of DAVID on the redesign of the site. We are responsible for drafting the specifications and overseeing the Junior Enterprise team (Paris-Saclay) in charge of the technical implementation of the project.
• Participation in doctoral mentorship training and research support programs
• Involved in doctoral support and awareness-raising activities
• UVSQ (2021 – current): Jury member of Master 2 DataScale deliberation panels, Paris-Saclay.
• UVSQ (2020 – current): Member of the panels responsible for assessing the skills and knowledge of Bachelor’s degrees in the « Sciences and Technologies » field.
• ISG, Tunis, Tunisia (2013 – 2017): Jury member of the BSc examination and deliberation committee and Jury member of MSc and BSc vivas
• FSEGN, Nabeul, Tunisia (2010 – 2013): Jury member of the BSc examination and deliberation committee and Jury member of BSc vivas
• Development of report templates (in LaTeX) for writing BCs project reports that are considered as standards at FSEGN.
• Development of report templates (in LaTeX) for writing master’s theses and doctoral dissertations that are considered as standards at ISG Tunis.

Master courses (Master 2, DataScale, Paris-Saclay)

• Data Mining. Lecturer. UE coordinator

• Project design – Hands-on practical sessions

• Project programming – Hands-on practical sessions

Bachelor courses

• Foundations of Computer Science I (Python), (L1). Lecturer & Hands-on practical sessions. UE coordinator

• Foundations of Computer Science II (Python), (L1) – Hands-on practical sessions

• Operating systems (L2) – Hands-on practical sessions

2023

TabSRA

An Attention based Self-Explainable Model for Tabular Learning [link]

2017

Sp-RST

A Distributed Rough Set Theory based Algorithm for an Efficient Big Data Pre-processing under the Spark Framework [link]

• Title: A federated learning approach for privacy of semantically enriched mobility data
  Keywords : Federated learning, Machine learning, Cybersecurity, IoT, Location privacy, Mobility data Mining ** position filled
• Title: Machine learning based approaches for multi-omics data in personalized treatment of sepsis
  Keywords: Machine learning, Bioinformatics pipeline, Dimentionality reduction, Clustering of multi-omics data, Multi-omics data, Personalized treatment of sepsis ** position filled

New PhDs positions will be coming soon.