- Teacher-researcher. Member of LabISEN.
Artificial intelligence
Smart Energy
Smart Objects
e-health & digital systems
Campus: Toulon
Core business
Passionate about artificial intelligence, I develop explainable models based on both expert knowledge and data-driven machine learning. My research focuses on Bayesian networks, embedded AI and their societal applications. In 2024, I obtained the authorization to register for the HDR around explanatory AI. Doctor in computer science since 2004 (University of Rouen), after a DEA in mathematical modeling and software engineering (2000, in partnership with the University of Rennes, EPFL, the Lebanese University and ESIB), I have devoted my career to teaching, research and innovation. I have supervised five doctoral theses and collaborated with a number of start-ups, notably in the creation of machine learning environments to foster innovation and technology transfer.
Prospective
My work follows an interdisciplinary trajectory, from fall prevention in Parkinson's patients (Université du Havre, 2013) to smart energy (fault detection in DC-DC converters), then to maritime cybersecurity and integrated circuits (Mines Saint-Étienne, 2024-2025), where I exploit picosecond-sensitive digital sensors to detect attacks. This foresight aims to anticipate the challenges of trust, robustness and explicability of AI in critical sectors, drawing on academic research, doctoral training and entrepreneurial innovation.
360°
My approach combines a solid academic foundation with a constant openness to industry and society. From neuromedicine to energy, from shipping to finance and secure embedded systems, my projects illustrate my ability to cross disciplines and contexts. Doctoral supervision and industrial partnerships reinforce this global vision. It leads me to train and support talents capable of designing AI that is at once critical, explainable and committed.
About Iyad Zaarour
Iyad Zaarour has been a lecturer and researcher in artificial intelligence since 2004. A specialist in Bayesian networks and the explicability of AI, he has gradually extended his research to a variety of application fields: finance, healthcare, energy, maritime, tourism, and more recently to secure embedded systems.
In addition to his academic and scientific activities, he is a veteran player and enthusiast of squash, table soccer and chess.
Research and development activities
- 2025
- (R&D) at Mines de Saint-Étienne, the Secured Systems and Architectures (SAS) team
- ADSEA project, " Distributed, intelligent and secure architecture in the maritime sector", 15 months, EMSE and two SMEs
- SPARTA project, " Detection of anomalies in integrated circuits", 6 months
- (R&D) at Mines de Saint-Étienne, the Secured Systems and Architectures (SAS) team
- 2023
- AI Architect at Divimah Startup - Greece
- 2023
- Responsible for mentors at the AUF (Agence Universitaire de la Francophonie) and active pedagogy on the Simplon methodology
- 2017
- Coordination and co-supervision in R&D with the GREAH team in Le Havre, the 'Saidat el maanounet' University Hospital, the 'Abraj' neurology center, the UL Faculty of Science, and the UI Khalde Biomedical Faculty.
Publications
Book Chapter
[1] I.Zaarour, A. Saad, M. Ayache, F.Guerin, P.Bejjani, D. Lefevbre, 2016, "Methodologies for the
Diagnosis of the Main Behavioral Syndromes for Parkinson Disease with Bayesian Belief Net. Publisher Elsevier[1]/Morgan Kaufmann, ISBN:978-0-12-802508-6
[1] Book Name "Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology - Algorithms and Software Tools".
Journal Publications
[2] A.Zein Eddine, F.Guerin, I.Zaarour, A.Hijazi, D.Lefebvre 2024 Fault Detection and Isolation in systems of Multiple-Sources of Energy using Hierarchal Bayesian Belief Network, Journal of Electrical Engineering EEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. Springer; ISSN:1432-0487; DOI: https://doi.org/10.1007/s00202-024-02472-y
[3] N.Fhaily, I.Zaarour, 2020, The Impact Of Basel III Capital Regulation on Credit Risk: A Hybrid Model, International Journal on Finance & Banking Studies IJFBS'2020, Vol. 9 No. 2, ISSN: 2147-4486 ; DOI: https://doi.org/10.20525/ijfbs.v9i2.722
[4] B.Dbouk, I. Zaarour, 2017, Towards a machine learning approach for earnings manipulation detection, The Asian Journal of Business and Accounting AJBA'2017, Vol. 10 No. 2 (2017); ISSN:19854064, 21803137; DOI: https://ejournal.um.edu.my/index.php/AJBA/article/view/9772
[5] B.Dbouk, I. Zaarour 2017, Financial Statements Earnings Manipulation Detection Using a Layer of Machine Learning, International Journal of Innovation, Management and Technology IJIMT'2017, Vol. 8, No. 3, June 2017, DOI: 10.18178/ijimt.2017.8.3.723
[6] M.Khreiss, I.Zaarour, H.Mcheik 2016, SMILE: smart monitoring intelligent learning engine: an ontology-based context-aware system for supporting patients subjected to severe emergencies, International Journal of Healthcare Technology and Management IJHTM'16, 15(3), pp. 194 -209, DOI: 10.1504/IJHTM.2016.078346.
[7] A.Saad, I.Zaarour, F.Guerin, P.Bejjani, M. Ayache, D. Lefebvre, 2016. Detection of freezing of gait for Parkinson's disease patients with multi-sensor device and Gaussian neural networks, International Journal of Machine Learning and Cybernetics, IJMLS'16- ISSN 1868-8071, DOI 10.1007/s13042-015-0480-0 Springer.
[8] A.Zein Eddine, I.Zaarour, F.Guerin, A.Hijazi, D.Lefebvre, 2016, A Comparative Study about the Effectiveness of Observers and Bayesian Belief Networks for the Fault Detection and Isolation in Power Electronics Research Journal of Applied Sciences, Engineering and Technology, 14(1):10-28; DOI:10.19026/rjaset.14.3984.
[9] A.Zein Eddine, I.Zaarour, F.Guerin, A.Hijazi, D.Lefebvre, 2015, Fault Detection and Isolation for ZVS Full Bridge Isolated Buck Converter Based on: Observer Design and Bayesian Network; International Journal of Advanced Research in Computer and communication Engineering Vol. 4, Issue 7, July 2015. ISSN (Online) 2278-1021; ISSN (Print) 2319-594. DOI: 10.17148/IJARCCE.2015.4755
[10] A. Saad, I. Zaarour, A. Zeinedine, M. Ayache, P. Bejjani, F. Guérin, D. Lefebvre 2013, A preliminary study of the causality of Freezing of Gait for Parkinson's disease patients: Bayesian Belief Network approach. IJCSI International Journal of Computer Science Issues, Vol. 10, Issue 3, No 2, P 88-95.
[11] A.Saad , I. Zaarour , P. Bejjani , M.Ayache 2012. Handwriting and Speech Prototypes of Parkinson Patients: Belief Network Approach. IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 3, May 2012 ISSN (Online): 1694-0814.
[12] Zaarour, B. El-Eter, P. Leray, L. Heutte, J. Labiche, D. Mellier, M. Zoater, 2005, A high-level modeling of motor writing strategies of primary school children: a Bayesian approach. Journal de Physique IV, vol. 124, pp. 233-236. DOI: 10.1051/jp4:2005124034
[13] Zaarour, L. Heutte, Ph. Leray, J. Labiche, B. Eter, D. Mellier, 2004, Clustering and bayesian network approaches for discovering handwriting strategies of primary school children, International Journal of Pattern Recognition and Artificial Intelligence, IJPRAI, vol. 18, no. 7, pp. 1233-1251. DOI https://doi.org/10.1142/S0218001404003745
Conferences
[14] Dbouk and I. Zaarour 2017. Financial Statements' Earnings Manipulation Detection Using A Layer of Machine Learning, ICETD'17.
[15] Zein Eddine, I.Zaarour, F.Guerin, A.Hijazi, D.Lefebvre, 2016. Improving Fault Isolation in DC/DC Converters Based with Bayesian Belief network IFAC'2016 (49-5) 303-308
[16] H. Mallah , I. Zaarour, A. KALAKECH. 2015 Toward a Preliminary Layered Network Model Representation of Medical Coding in Clinical Decision Support Systems, HIMS'15, The 2015 International Conference on Health Informatics and Medical Systems.
[17] H.Mcheik M.Khreiss, I.Zaarour, H.Sweidan, 2015. PHEN: Parkinson Helper Emergency Notification System Using Bayesian Belief Network, 6th International Conference on E-Technologies MCETECH 2015: E-Technologies pp 212-223
[18] A.Saad, I. Zaarour, F. Guerin, M. Ayache, D. Lefebvre. 2014 'Sensoring and Features Extraction for the Detection of Freeze of Gait in Parkinson Disease'. IEEE 11th International Multi-Conference on Systems, Signals & Devices (SSD). Barcelona, Spain
[19] Ali Saad, Iyad Zaarour, Dimitri Lefebvre, François Guerin, Paul Bejjani, Mohammad Ayache. About Detection and Diagnosis of Freezing of Gait'. IEEE 2nd International Conference on Advances in Biomedical Engineering. 2013.
[20] A.Fouladcar, I.Zaarour, 2013. Toward Multidimensional modeling in Healthcare, World Summit on Big Data and Organization Design, May 16-17, 2013, Sorbonne- Paris.
[21] Saad, I. Zaarour, A. Zeinedine, M. Ayache, P. Bejjani, F. Guerin, D.Lefebvre. 'A Preliminary Study of the Causality of Freezing of Gait for Parkinson's Disease Patients: Bayesian Belief Network Approach', DMIN13, 2013.
[22] Saad, I. Zaarour, P. Bejjani, M. Ayache, 2012. Handwriting and Speech Prototypes for Parkinson Patients: Belief Network Approach; SETIT'2012.Sousse 21-24-March-Tunisia:
[23] Zaarour, Z. Saliha, L. Heutte, D. Mellier. Online acquisition and comparison of bilingual children's handwriting. 8th International Colloquium on the Digital Document, CIDE 8, Beirut, Lebanon, pp. 65-72, 2005.
[24] Zaarour, P. Leray, L. Heutte, B. Eter, J. Labiche, D. Mellier, M. Zoaeter. Modelling of handwriting prototypes in graphonomics : Bayesian network approach. 5th EUROSIM Congress on Modelling and Simulation, EUROSIM'04, Marne-la-Vallée, France, pp. 78 (Proceedings on CD-ROM), 2004.
[25] P. Leray, I. Zaarour, L. Heutte, B. El-Eter, J. Labiche, D. Mellier. Bayesian networks for the discovery of handwriting strategies in elementary school children. 14ème Congrès Francophone AFRIF-AFIA de Reconnaissance des Formes et Intelligence Artificielle, RFIA'2004, Toulouse, France, vol. 3, pp. 1135-1142, 2004.
[26] Zaarour, L. Heutte, B. El-Eter, J. Labiche, D. Mellier, P. Leray, M. Zoaeter. A probabilistic modeling of the writing strategies evolution for pupils in primary education. 11th Conference of the International Graphonomics Society, IGS'2003, Scottsdale, Arizona, pp. 174-177, 2003.
[27] Zaarour, P. Leray, L. Heutte, B. El-Eter, J. Labiche, D. Mellier. A bayesian network model for discovering handwriting strategies of primary school children. 11th Conference of the International Graphonomics Society, IGS'2003, Scottsdale, Arizona, pp. 178-181, 2003.
[28] P. Leray, I. Zaarour, L. Heutte, B. El-Eter, J. Labiche, D. Mellier. A bayesian model for discovering handwriting strategies of primary school children. Workshop on Probabilistic Graphical Models for Classification, ECML/PKDD-2003, Cavtat-Dubrovnik, Croatia, pp. 49-57, 2003.
[29] Zaarour, L. Heutte, B. Eter, J. Labiche, D. Mellier, M. Zoaeter. A probabilistic modeling of the evolution of students' writing strategies in primary school. First International Congress on Applied Numerical Modeling, CIMNA'2003, Beirut, Lebanon, pp. 383-388, 2003.
[30] Zaarour, P. Leray, D. Mellier, J. Labiche, L. Heutte. Graphomotor strategies models and their evolution at the primary school: approach by bayesian networks. Progress in Motor Control IV: Motor Control and Learning over the Life Span, Caen, France, pp. 174, 2003