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Habib HADJ-MABROUK

Chercheur en intelligence artificielle et sécurité ferroviaire

Présidence / Vice-présidence Recherche

Marne-la-Vallée

Bâtiment: Building: Bienvenüe

14-20 Boulevard Newton
Champs-sur-Marne
77447 Marne-la-Vallée Cedex 2

Bureau: Office: C229

https://cv.archives-ouvertes.fr/habib-hadj-mabrouk https://orcid.org/0000-0001-9322-8175 https://scholar.google.fr/citations?hl=fr&user=aFq1RTwAAAAJ&view_op=list_works&sortby=pubdate https://univ-gustave-eiffel.academia.edu/HabibHADJMABROUK https://www.researchgate.net/profile/Habib_Hadj-Mabrouk

Habib HADJ-MABROUK

Chercheur en intelligence artificielle et sécurité ferroviaire

Présidence / Vice-présidence Recherche

  • 1992 : Doctorat en en automatique et informatique des systèmes industriels et humains, Université Polytechnique Hauts-de-France (UPHF) 
  • 1998 : Habilitation à Diriger des Recherches (HDR), Université de technologie de Compiègne
  • 1993 à 2010 : Chercheur à l’INRETS
  • 2011 à 2019 : Chercheur à l’IFSTTAR 
  • Depuis 2020 :  Chercheur à l’Université Gustave Eiffel

QUALIFICATIONS:

  • 1998: HDR – "Accreditation to supervise research" in Railway Safety and Artificial Intelligence. University of Technology Compiègne (France);
  • 1992: PhD – in Automatic and Computer Science of Industrial and Human Systems. Polytechnic University of Hauts-de-France;
  • 1989: DEA – "Diploma of Thorough Studies" in Automatic and industrial Maintenance. University of Valenciennes (France).

FUNCTIONS:

  • Since 2020, Researcher at University Gustave Eiffel, Department: Vice-Presidency Research;
  • 2011-2019, Researcher at French Institute of Science and Technology for Transport, Development and Networks (IFSTTAR), Department: Scientific Direction;
  • 1993-2010: Researcher at French National Institute for Transport and Safety Research (INRETS), Department: Evaluation of Automated Transport Systems and their Safety (ESTAS).

Mes dernières références

My latest references

Publications sélectionnées en intelligence artificielle et sécurité ferroviaire

Selected Publications in Artificial Intelligence and Railway Safety

1. Hadj-Mabrouk, H. (2026). Artificial Intelligence and Machine Learning in Railway Operations, Maintenance, and Safety: Contributions, Challenges, and Limitations. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 240(1), pp. 3–36. DOI: https://doi.org/10.1177/1748006X251364324. Indexage: Web of Science (SCIE), Scopus

2. Hadj-Mabrouk, H. (2025). Expert System Based on Ontology and Interpretable Machine Learning to Assist in the Discovery of Railway Accident Scenarios. Computers, Materials & Continua, 84(3), pp. 4399–4430. DOI: https://doi.org/10.32604/cmc.2025.067143. Indexage: Web of Science (SCIE), Scopus

3. Hadj-Mabrouk, H. (2024). A Literature Review on the Applications of Artificial Intelligence to European Rail Transport Safety. IET Intelligent Transport Systems, 18(12), pp. 2291–2324. DOI: https://doi.org/10.1049/itr2.12587. Indexage: Web of Science (SCIE), Scopus

4. Hadj-Mabrouk, H. (2024). Literature Review on Applications of Ontologies and Knowledge Graphs in Railway Transport Safety. In: Railway Transport and Engineering, IntechOpen. DOI: https://doi.org/10.5772/intechopen.1006278. Indexage: Book chapter

5. Hadj-Mabrouk, H. (2023). Approach to Assist in the Discovery of Railway Accident Scenarios Based on Supervised Learning. In: Transportation Energy and Dynamics, Springer, pp. 129–156. DOI: https://doi.org/10.1007/978-981-99-2150-8_7. Indexage: Scopus (Springer)

6. Hadj-Mabrouk, H. (2021). Case-based reasoning for safety assessment of critical software. Intelligent Decision Technologies, 14(4), pp. 463–479. DOI: https://doi.org/10.3233/IDT-200016. Indexage: Scopus

7. Hadj-Mabrouk, H. (2021). Contribution of Machine Learning to Rail Transport Safety. In: Advances of Machine Learning in Clean Energy and the Transportation Industry, Nova Science Publishers, pp. 277–312. DOI: https://doi.org/10.52305/SJDR3905. Indexage: Book chapter

8. Hadj-Mabrouk, H. (2021). Human Factors Affecting Railway Safety: Approach for Considering Human Errors in Investigations. In: Handbook of Research on Decision Sciences and Applications in the Transportation Sector, IGI Global. DOI: https://doi.org/10.4018/978-1-7998-8040-0. Indexage: Book chapter

9. Hadj-Mabrouk, H. (2021). Decision Support Approach for Assessing Rail Transport Safety Using AI and ML. In: Handbook of Research on Decision Sciences and Applications in the Transportation Sector, IGI Global. DOI: https://doi.org/10.4018/978-1-7998-8040-0. Indexage: Book chapter

10. Hadj-Mabrouk, H. (2020). Application of Case-Based Reasoning to the safety assessment of critical software used in rail transport. Safety Science, 131, 104928. DOI: https://doi.org/10.1016/j.ssci.2020.104928. Indexage: Web of Science (SCIE), Scopus

11. Hadj-Mabrouk, H. (2020). Analysis and Prediction of Railway Accident Risks Using Machine Learning. AIMS Electronics and Electrical Engineering, 4(1), pp. 19–46. DOI: https://doi.org/10.3934/ElectrEng.2020.1.19. Indexage: Scopus

12. Hadj-Mabrouk, H. (2019). Contribution of Artificial Intelligence to Risk Assessment of Railway Accidents. Urban Rail Transit, 5(2), pp. 104–122. DOI: https://doi.org/10.1007/s40864-019-0102-3. Indexage: Scopus, ESCI

13. Hadj-Mabrouk, H. (2019). A Hybrid Approach for the Prevention of Railway Accidents Based on Artificial Intelligence. In: Intelligent Computing & Optimization (ICO 2018), Springer, pp. 383–394. DOI: https://doi.org/10.1007/978-3-030-00979-3_41. Indexage: Scopus

14. Hadj-Mabrouk, H. (2019). Contribution of Artificial Intelligence and Machine Learning to the Safety Assessment of Critical Software. AIMS Electronics and Electrical Engineering, 3(1), pp. 33–70. DOI: https://doi.org/10.3934/ElectrEng.2019.1.33. Indexage: Scopus

15. Hadj-Mabrouk, H. (2018). A Hybrid Approach for the Prevention of Railway Accidents Based on Artificial Intelligence. In: Intelligent Computing & Optimization, Springer, pp. 383–394. DOI: https://doi.org/10.1007/978-3-030-00979-3_41. Indexage: Scopus

16. Hadj-Mabrouk, H. (2017). Contribution of Learning CHARADE System of Rules for the Prevention of Rail Accidents. Intelligent Decision Technologies, 11(4), pp. 477–485. DOI: https://doi.org/10.3233/IDT-170304. Indexage: Scopus


1. Hadj-Mabrouk, H. (2026). Artificial Intelligence and Machine Learning in Railway Operations, Maintenance, and Safety: Contributions, Challenges, and Limitations. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 240(1), pp. 3–36. DOI: https://doi.org/10.1177/1748006X251364324. Indexage: Web of Science (SCIE), Scopus

2. Hadj-Mabrouk, H. (2025). Expert System Based on Ontology and Interpretable Machine Learning to Assist in the Discovery of Railway Accident Scenarios. Computers, Materials & Continua, 84(3), pp. 4399–4430. DOI: https://doi.org/10.32604/cmc.2025.067143. Indexage: Web of Science (SCIE), Scopus 

3. Hadj-Mabrouk, H. (2024). A Literature Review on the Applications of Artificial Intelligence to European Rail Transport Safety. IET Intelligent Transport Systems, 18(12), pp. 2291–2324. DOI: https://doi.org/10.1049/itr2.12587. Indexage: Web of Science (SCIE), Scopus

4. Hadj-Mabrouk, H. (2024). Literature Review on Applications of Ontologies and Knowledge Graphs in Railway Transport Safety. In: Railway Transport and Engineering, IntechOpen. DOI: https://doi.org/10.5772/intechopen.1006278. Indexage: Book chapter

5. Hadj-Mabrouk, H. (2023). Approach to Assist in the Discovery of Railway Accident Scenarios Based on Supervised Learning. In: Transportation Energy and Dynamics, Springer, pp. 129–156. DOI: https://doi.org/10.1007/978-981-99-2150-8_7. Indexage: Scopus (Springer)

6. Hadj-Mabrouk, H. (2021). Case-based reasoning for safety assessment of critical software. Intelligent Decision Technologies, 14(4), pp. 463–479. DOI: https://doi.org/10.3233/IDT-200016. Indexage: Scopus

7. Hadj-Mabrouk, H. (2021). Contribution of Machine Learning to Rail Transport Safety. In: Advances of Machine Learning in Clean Energy and the Transportation Industry, Nova Science Publishers, pp. 277–312. DOI: https://doi.org/10.52305/SJDR3905. Indexage: Book chapter

8. Hadj-Mabrouk, H. (2021). Human Factors Affecting Railway Safety: Approach for Considering Human Errors in Investigations. In: Handbook of Research on Decision Sciences and Applications in the Transportation Sector, IGI Global. DOI: https://doi.org/10.4018/978-1-7998-8040-0. Indexage: Book chapter

9. Hadj-Mabrouk, H. (2021). Decision Support Approach for Assessing Rail Transport Safety Using AI and ML. In: Handbook of Research on Decision Sciences and Applications in the Transportation Sector, IGI Global. DOI: https://doi.org/10.4018/978-1-7998-8040-0. Indexage: Book chapter

10. Hadj-Mabrouk, H. (2020). Application of Case-Based Reasoning to the safety assessment of critical software used in rail transport. Safety Science, 131, 104928. DOI: https://doi.org/10.1016/j.ssci.2020.104928. Indexage: Web of Science (SCIE), Scopus

11. Hadj-Mabrouk, H. (2020). Analysis and Prediction of Railway Accident Risks Using Machine Learning. AIMS Electronics and Electrical Engineering, 4(1), pp. 19–46. DOI: https://doi.org/10.3934/ElectrEng.2020.1.19. Indexage: Scopus

12. Hadj-Mabrouk, H. (2019). Contribution of Artificial Intelligence to Risk Assessment of Railway Accidents. Urban Rail Transit, 5(2), pp. 104–122. DOI: https://doi.org/10.1007/s40864-019-0102-3. Indexage: Scopus, ESCI

13. Hadj-Mabrouk, H. (2019). A Hybrid Approach for the Prevention of Railway Accidents Based on Artificial Intelligence. In: Intelligent Computing & Optimization (ICO 2018), Springer, pp. 383–394. DOI: https://doi.org/10.1007/978-3-030-00979-3_41. Indexage: Scopus

14. Hadj-Mabrouk, H. (2019). Contribution of Artificial Intelligence and Machine Learning to the Safety Assessment of Critical Software. AIMS Electronics and Electrical Engineering, 3(1), pp. 33–70. DOI: https://doi.org/10.3934/ElectrEng.2019.1.33. Indexage: Scopus

15. Hadj-Mabrouk, H. (2018). A Hybrid Approach for the Prevention of Railway Accidents Based on Artificial Intelligence. In: Intelligent Computing & Optimization, Springer, pp. 383–394. DOI: https://doi.org/10.1007/978-3-030-00979-3_41. Indexage: Scopus

16. Hadj-Mabrouk, H. (2017). Contribution of Learning CHARADE System of Rules for the Prevention of Rail Accidents. Intelligent Decision Technologies, 11(4), pp. 477–485. DOI: https://doi.org/10.3233/IDT-170304. Indexage: Scopus