BENATIA Mohamed Amin


Mohamed Amin BENATIA, associate professor at CESI engineering school  (Rouen- France).

He's working on Big Data management for knowledge discovery applications running on clouds within the LINEACT research Lab, under the supervision of Pr. Anne LOUIS. His research interest is on Deep Learning models applied to industrial domains (fault tolerance, maintenance, etc.). He was a PhD student at INSA (Rouen, France), under the supervision of Pr. Abdelkhalak EL-HAMI and Pr. Anne LOUIS, and a part-time assistant teacher at Ei. CESI, Rouen-FRANCE.

His PhD subject was on Multi-Objective WSN deployment for indoor applications (smart building).

He obtained his Master degree in 2012 (computer networks, distributed computing) at University of Pierre and Marie Curie (Paris - France).


  • Knowledge discovery
  • Deep learning
  • Big Data
  • Operations Research
  • Artificial Intelligence
  • Intelligent Maintenance Systems

0 (33) 7 63 49 94 11

80 Rue Edmund Halley,
76800, Saint Etienne du Rouvray

Research themes

Engineering and Digital Tools

  • Industry of the future (Industry 4.0)
  • Artificial Intelligence
  • Predictive maintenance
  • Supply Chain Management
  • Business Intelligence

Educational activities

  • Disciplines: Data Fusion, Machine Learning, Operations Research (OR), Artificial Intelligence
  • Level: Engineers, Bachelor AI, DU AI & Health
  • Discipline: Mathematics, Statistics and Probability, Business Intelligence
  • Level: Engineers, Bachelor IA


Phd. In Computer Science

INSA de Rouen


Master 2 – Computer Networks

Université de Pierre et Marie Curie (Paris 6)


Ingineer in Computer Science (Artificial Intelligence)

Université de Biskra


Current research programmes

  • Smart Mobility: This project aims to develop new autonomous, decarbonised, digital and shared mobility systems. In this context, we are working on the planning and supervision of a multimodal transport system.
  • Plate-Forme de Performances Industrielles (PFPI): Design of a Industry 4.0 demonstrator in the context of the chair CESI-CISCOVINCI.
  • VISTA-AR: This project will develop and implement a range of exciting Augmented Reality (AR) and Virtual Reality (VR) experiences for a number of visitors attractions in the South of England and the North of France.
  • Défi & Co : The project "Developing Future Expertise for Industry and Construction" (DEFI&Co) aims to carry out collaborative industrial research to design training systems for new trades related to the industry of the future, the building of the future, and the massive data processing required for their implementation; to monitor the experimental development of these training systems throughout the national territory; and to guide the evolution and improvement of these systems once they have been deployed on a large scale.

Internship supervision

  • Internships
    • F. E. KEDDOUS “Géolocalisation de personnes pour des visites de sites et bâtiments” (2017)
    • BOUCHAOUR El-Hadi “ Etudes et réalisations autour d’une solution Big Data pour l’analyse et le monitoring des données touristiques” (2018)
    • ALIOUA Salim “Fusion de données capteurs pour la géolocalisation de personnes dans des environnements indoor” (2018)
    • PAGNA Sylvère « Localisation Indoor des personnes en se basant sur le champs magnétique » (2019)
    • MENACER Nasreddine « Prédiction de la qualité d’un câble de fibre optique par fusion de données capteurs » (2020)
    • SAHBANI Bouchra « Réduction du nombre d’alerte maintenance par deep learning » (2020)
  • Phd Students
    • SAHBANI Bouchra "Supervision prédictive d'un système de transport multimodal" (en cours)
    • AMAL AYADI "Diagnostic et Pronostic à l'aide de l'IA dans le cadre de la maintenance industrielle" (en cours)

Scientic animation and laboratory life

  • Participation in the setting up of projects (RIN-SupAction, Interreg, etc.)
  • Proposal for a special session on digital tourism (MetroArcheo '18)
  • Participation in the scientific committee of the CyMaEn'21 conference
  • Participation in science forums and Open-Days
  • Member of the GDRs: COS (stochastic optimisation) and MADICS.



  • [RI 1] BENATIA, M. A., SAHNOUN, M., LOUIS, A., BAUDRY, D., MAZARI, M., & EL-HAMI, “Multi-Objective WSN Deployment Using Genetic Algorithms under Cost, Coverage, and Connectivity Constraints”. Wireless Personal Networks Journal (Springer),(2017) pp. 1-30
  • [RI 2] BENATIA M., BAUDRY, D., LOUIS, A., “ Detecting counterfeit products by means of frequent pattern mining”, Ambient Intelligence & Humanized Computing (AIHC), Springer, 2020
  • [RI 3] Shekhawat, R. S., Benatia, M. A., & Baudry, D. (2021). A Novel Strategy for Energy Optimal Designs of IoT and WSNs. In Advances in Machine Learning and Computational Intelligence (pp. 603-610). Springer, Singapore.
  • [RI 4] Brik, B., Messaadia, M., Sahnoun, M. H., Bettayeb, B., & Benatia, M. A. (2021). Fog-supported Low Latency Monitoring of System Disruptions in Industry 4.0: A Federated Learning Approach. ACM Transactions on Cyber-Physical Systems.

  International Conferences

  • [CI 1] – BENATIA, M. A., BAUDRY, D., LOUIS, A., « Alarm Correlation to Improve Industrial Fault Management », IFAC World Congress 2020 [CI 2] – BENATIA, M. A., A. REMADNA, BAUDRY, D., HALFTERMEYER, P., DELALIN, H., “ QR-code enabled product traceability system: A big data perspective”, International Conference in Manufacturing research (ICMR’18), 2018
  • [CI 3] – REMADNA, A., BENATIA, M. A., LOUIS, A., GOUT, C., ”A Predictive Analysis Data-Based for Additive Manufacturing”, International Conference in Manufacturing research (ICMR’18), 2018
  • [CI 4] – ALIOUA, S., MESSAADIA, M, BENATIA, M. A., SAHNOUN, S. SMART, A., ”Indoor geolocation based on earth magnetic field”, IEEE International Conference on Metrology for Archaeology and Cultural Heritage (MetroArchaeo), (2018)
  • [CI 5] – BENATIA, M. A., DE SA, V. E., BAUDRY, D., DELALIN, H., HALFTERMEYER, P., “A framework for Big Data driven product traceability system”, IEEE INTERNATIONAL CONFERENCE on ADVANCED TECHNOLOGIES FOR SIGNAL& IMAGE PROCESSING (ATSIP’18), 2018.
  • [CI 6] – BENATIA, M., SAHNOUN, M., LOUIS, A., BAUDRY, D., MAZARI, M., & EL-HAMI, “Impact of radio propagation in buildings on WSN's lifetime”, IEEE Global Summit on Computer & Information Technology (GSCIT), 2014.
  • [CI 7] - BENATIA, M., SAHNOUN, M., LOUIS, A., BAUDRY, D., MAZARI, M., & EL-HAMI, A. Optimized Sink node Deployment in WSN Using Genetic Algorithms through Coverage and Cost Constraints. META’14 (2014)
  • [CI 8] - BENATIA, M.A.; Louis, A.; Baudry, D.; Mazari, B.; El Hami, A., "WSN's modeling for a smart building application," Energy Conference (ENERGYCON), 2014 IEEE International, vol., no., pp.821,827, 13-16 May 2014.
  • [CI 9] - Belahcene, M., Chouchane, A., BENATIA, M. A., & Halitim, M. (2014, November). “3D and 2D face recognition based on image segmentation”. In Computational Intelligence for Multimedia Understanding (IWCIM), 2014 International Workshop on (pp. 1-5). IEEE.
  • [CI 10] - BENATIA, M. A., Khoukhi, L., Esseghir, M., & Boulahia, L. M. (2013, March). A Markov chain based model for congestion control in VANETs. In Advanced Information Networking and Applications Workshops (WAINA), 2013 27th International Conference on (pp. 1021-1026). IEEE.

  National Conferences 

  • [CN 2] SAHNOUN, M., BETTAYEB B, BENATIA MA, BRIK B, « un processus décisionnel basé sur la localisation de ressources pour la planification dynamique des tâches », ROADEF’19
  • [CN 3] M, MESSAADIA, M, SAHNOUN, MA, BENATIA, « recommandation de parcours de visiteurs dans les sites historiques basée sur le q-learning », ROADEF’19
  • [CN 1] - BENATIA, M., SAHNOUN, M., LOUIS, A., BAUDRY, D., MAZARI, M., & EL-HAMI , Méta heuristiques pour le Placement Optimisé des Nœuds Routeur Dans un Réseau de Capteurs Sans Fil, ROADEF’15.

  Rapports scientifiques ou techniques

  • [RS 1] Rapport de soutenance de thèse : « Optimisation multiobjectives d’une infrastructure réseau dédiée aux bâtiments intelligents » (soutenue en 2016) [RS 2] Rapports du projet INTERREG IVA CREST



Artificial Intelligence


Machine Learning/Deep Learning


Operations Research


Predictive Maintenance