Dr. Rabih Amhaz

Profile

I am an associate professor and AI research lead at Icam Strasbourg-Europe and a member of the ICube laboratory at the University of Strasbourg.

My research is multimodal AI for human-machine interfaces and trustworthy AI, applied to images, video, text and graph data. I led Icam Strasbourg-Europe's digital department for two years, and since 2019 I have created two specialised master's programmes in Industry 4.0 and IoT.

Before that, from 2016 to 2019, I was part of the small founding team that built UFAZ, the French-Azerbaijani University in Baku, as a branch of the University of Strasbourg, and founded its computer science curriculum.

I also founded RA Development, where I build AI education and products, and I have worked as an educational engineer since 2016.

Career

• 2015PhD in computer science, Centrale Nantes
  Automatic crack detection on pavement images by minimal path selection
• 2016 to 2019Founding team of UFAZ, Baku
  Built the computer science curriculum of the French-Azerbaijani University
• Since 2019Icam Strasbourg-Europe
  Two specialised master's created, now MS-ASPII; head of the digital department for two years
• TodayAssociate professor, AI research lead
  Icam and ICube, University of Strasbourg

Research

• HABIT, SkyMind, VivaTech 2025 studyMultimodal AI and human factors
  Learning from real behaviour: gaze, hand motion, posture and neurocognitive signals, recorded where people actually work.
• speGAI, Explainable intrusion detectionTrustworthy and explainable AI
  AI people can question. Explainability metrics for security models, and generative agents limited to specific, ethical tasks.
• AI for automotive data, Anomaly detection on graphsGraphs and complex systems
  Data where relations matter as much as values: graph neural networks, dynamic graphs and graph-tabular fusion.
• MIIRAG, Laser weld predictionVision for infrastructure and industry
  Where my research started: detecting thin cracks in pavement images, now extended to industrial inspection and safety.

Publications

1. V. Hayot, R. Amhaz, S. Lecler, A. Alves Ferreira, G. Chabrol (2025). Machine learning for prediction of laser welds penetration on a multi-material dataset. International Journal of Advanced Manufacturing Technology 140, 2895-2907. DOI 10.1007/s00170-025-16437-3.
2. V. Hayot, R. Amhaz, S. Lecler, A. Alves Ferreira, G. Chabrol (2024). Interest of data augmentation in AI-prediction of metal laser welding penetration. Research Square preprint. DOI 10.21203/rs.3.rs-5204448/v1.
3. R. Amhaz, C. Bobenrieth, M. Marz (2024). Impact of decentralized autonomous organizations (DAO) on society 5.0. NET 2024, Dubai. DOI 10.5121/csit.2024.140301.
4. A. Abou Rida, R. Amhaz, P. Parrend (2023). Metrics for evaluating interface explainability models for cyberattack detection in IoT data. CCE 2023. DOI 10.1007/978-3-031-44355-8_13.
5. R. Fatali, S. Elzant, R. Amhaz (2023). A comparative study of YOLO v4 and v5 architectures on pavement cracks using region-based detection. CCE 2023. DOI 10.1007/978-3-031-44355-8_4.
6. A. Abou Rida, R. Amhaz, P. Parrend (2023). A benchmark for explainability of machine learning for cyberattacks detection. RESSI 2023, GDR Sécurité Informatique.
7. A. Abou Rida, R. Amhaz, P. Parrend (2022). Anomaly detection on static and dynamic graphs using graph convolutional neural networks. Robotics and AI for Cybersecurity and Critical Infrastructure in Smart Cities, Springer. DOI 10.1007/978-3-030-96737-6_12.
8. A. Abou Rida, R. Amhaz, P. Parrend (2022). Evaluation of anomaly detection for cybersecurity using inductive node embedding with convolutional graph neural networks. Complex Networks 2021, Madrid. DOI 10.1007/978-3-030-93413-2_47.
9. U. Abdulkarimova, I. Santos Peretta, A. Leonteva, Y. Monjid, R. Amhaz, M. Haegelin, P. Collet, C. Rolando (2020). A GA for non-uniform sampling harmonic analysis. GECCO 2020, ACM. DOI 10.1145/3377929.3390008.
10. L. Yang, V. Baltazart, R. Amhaz, P. Jiang (2016). A new A-star algorithm adapted to the semi-automatic detection of cracks within grey level pavement images. ICDIP 2016. DOI 10.1117/12.2243982.
11. V. Baltazart, J.-M. Moliard, R. Amhaz, M. Jethwa (2016). Automatic crack detection on pavement images for monitoring road surface conditions: results from the FP7 TRIMM project. RILEM Bookseries. DOI 10.1007/978-94-024-0867-6_100.
12. R. Amhaz, S. Chambon, J. Idier, V. Baltazart (2015). Automatic crack detection on 2D pavement images: an algorithm based on minimal path selection. IEEE Transactions on Intelligent Transportation Systems. DOI 10.1109/TITS.2015.2477675.
13. R. Amhaz, S. Chambon, J. Idier, V. Baltazart (2014). A new minimal path selection algorithm for automatic crack detection on pavement images. IEEE International Conference on Image Processing (ICIP). DOI 10.1109/ICIP.2014.7025158.
14. R. Amhaz, S. Chambon, J. Idier, V. Baltazart (2013). Une méthode de relevé automatique de fissures de chaussée fondée sur la recherche de chemins minimaux. HAL. https://hal.science/hal-01202525
15. R. Amhaz, S. Chambon, J. Idier, V. Baltazart (2013). Automatic road crack detection by selection of minimal paths. HAL. https://hal.science/hal-01197285

Conferences and workshops

• 18 November 2025After attention, what will the MIND complex system do next?
  Visionary lecture, University of Fribourg, Digital Neuroscience Master
• 18 to 19 June 2025Industrial Digital Transition session
  Session chair, Icam International Research Days (2IRD 2025), Strasbourg
• 25 September 2024The art of the prompt for generative AI
  Conference, Icam Toulouse amphitheatre
• April 2024Three prizes with team VerbaVite
  Hackathon coach, Hacking Health Camp 2024, Strasbourg
• 2024Trusted generative AI for cybersecurity
  Public conference, Palais du Gouverneur Militaire de Strasbourg, with Icam Alumni
• 11 October 2023Research in AI and the role of industry
  Conference, Icam Strasbourg-Europe

• The trilogy of technology for e-logistics jobs, UVSQ master's in logistics
• Teaching and training jobs in the era of generative AI, CSFC Grand Est
• Demystifying generative AI and its ecological impact
• Immersive VR, AR and mixed reality in industry and AI research
• Cybersecurity careers webinar, Grand Est orientation service

Development projects

• nabux.orgNabuX: A learning game for understanding AI
• enkiz.orgFaheem: An AI assistant that answers from a business's own data
• app.radevelopment.netRaDev Community: A community for tech between France and MENA

Media

• Documentary on the NotPetya cyberattack — Alaraby TV, Kontu Hunak
• Can we trust AI? — The Brain Factory podcast
• AI in European refugee planning and decisions — InfoMigrants
• Artificial intelligence: evolution or revolution? — Icam Liaisons 209