Mehdi Saman Azari
Postdoctoral Fellow
Department of Computer Science and Media Technology
Faculty of Technology
My research groups
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Cyber-Physical Systems (CPS) The CPS research group is responsible for research, teaching, and outreach activities in the field of Cyber-Physical Systems.
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Engineering Resilient Systems (EReS) The Engineering Resilient Systems (EReS) Research Lab conducts research in the area of system resilience. It focuses on investigating (and experimenting with)…
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Smart Industry Group Smart Industry Group (SIG) is an interdisciplinary research group featuring expertise from computer science and mechanical engineering. SIG's focus is making production and…
Publications
Article in journal (Refereed)
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Saman Azari, M., Santini, S., Edrisi, F., Flammini, F. (2025). Self-adaptive fault diagnosis for unseen working conditions based on digital twins and domain generalization. Reliability Engineering & System Safety. 254 (Part A).
Status: Published -
Saman Azari, M., Ricci, L., Santini, S., Flammini, F. (2025). An Intelligent Diagnostic Framework Based on Digital Twins and Partial Transfer Learning : Methodology and Industrial Application. IEEE Transactions on Industrial Cyber-Physical Systems. 3. 1-13.
Status: Published -
Dirnfeld, R., De Donato, L., Somma, A., Saman Azari, M., Marrone, S., et al. (2024). Integrating AI and DTs : challenges and opportunities in railway maintenance application and beyond. Simulation (San Diego, Calif.). 100 (9). 903-917.
Status: Published -
De Donato, L., Dirnfeld, R., Somma, A., De Benedictis, A., Flammini, F., et al. (2023). Towards AI-assisted digital twins for smart railways : preliminary guideline and reference architecture. Journal of Reliable Intelligent Environments. 9 (3). 303-317.
Status: Published -
Rajabi, S., Saman Azari, M., Santini, S., Flammini, F. (2022). Fault diagnosis in industrial rotating equipment based on permutation entropy, signal processing and multi-output neuro-fuzzy classifier. Expert systems with applications. 206.
Status: Published -
Singh, P., Saman Azari, M., Vitale, F., Flammini, F., Mazzocca, N., et al. (2022). Using log analytics and process mining to enable self-healing in the Internet of Things. Environment Systems and Decisions. 42 (2). 234-250.
Status: Published -
Saman Azari, M., Ramezani, A., Rajabi, S., Chaibakhsh, A. (2012). Using One-Class Support Vector Machine for the Fault Diagnosis of an Industrial Once-Through Benson Boiler. The Modares Journal of Electrical Engineering. 12 (3). 39-45.
Status: Published
Conference paper (Refereed)
- Edrisi, F., Saman Azari, M. (2023). Digital Twin for Sustainability Assessment and Policy Evaluation : A Systematic Literature Review. 2023 IEEE/ACM 7th International Workshop on Green And Sustainable Software (GREENS). 1-8.
- Saman Azari, M., Flammini, F., Santini, S. (2022). Improving Resilience in Cyber-Physical Systems based on Transfer Learning. 2022 IEEE International Conference on Cyber Security and Resilience (CSR). 203-208.
- Dirnfeld, R., De Donato, L., Flammini, F., Saman Azari, M., Vittorini, V. (2022). Railway Digital Twins and Artificial Intelligence : Challenges and Design Guidelines. Dependable Computing – EDCC 2022 Workshops. EDCC 2022. 102-113.
- Singh, P., Flammini, F., Caporuscio, M., Saman Azari, M., Thornadtsson, J. (2020). Towards self-healing in the internet of things by log analytics and process mining. Proceedings of the 30th European Safety and Reliability Conference and the 15th Probabilistic Safety Assessment and Management Conference. 4644-4651.
- Saman Azari, M., Flammini, F., Caporuscio, M., Santini, S. (2019). Data-Driven Fault Diagnosis of Once-through Benson Boilers. 2019 4th International Conference on System Reliability and Safety (ICSRS). 345-354.
- Saman Azari, M., Rajabi, S., Ramezani, A., Chaibakhsh, A. (2016). Fault diagnosis of an industrial once-through benson boiler by utilizing adaptive neuro-fuzzy inference system. 2016 6th Conference on Thermal Power Plants (CTPP). 32-37.
- Rajabi, S., Saman Azari, M., Momeni, H., Ramezani, A. (2016). Automated fault diagnosis of rolling element bearings based on morphological operators and M-ANFIS. 24th Iranian Conference on Electrical Engineering (ICEE). 1757-1762.
Chapter in book (Refereed)
- Assenza, G., Cozzani, V., Flammini, F., Gotcheva, N., Gustafsson, T., et al. (2020). White Paper on Industry Experiences in Critical Information Infrastructure Security : A Special Session at CRITIS 2019. Critical Information Infrastructures Security14th International Conference, CRITIS 2019, : Linköping, Sweden, September 23–25, 2019, Revised Selected Papers. Springer. 197-207.
Article, review/survey (Refereed)
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Saman Azari, M., Flammini, F., Santini, S., Caporuscio, M. (2023). A Systematic Literature Review on Transfer Learning for Predictive Maintenance in Industry 4.0. IEEE Access. IEEE. 11. 12887-12910.
Status: Published