Sania Partovian, Industrial Doctoral Student
Sania is a multidisciplinary-oriented by education and experience, she has been exposed to a number of diverse working environments and academia in the field of Artificial Intelligence and Mechateronics.Holding a master degree in Mechatronics and study basic of mechanic engineering and electrical engineering broaden her horizon to to continuously extend her knowledge and develop novel methods and apply them to solve real world problems.Currently, she is following his research interests as a Ph.D. candidate in Mälardalens University (MDH) and as a researcher in the Sigma Technology.
Her main research subject is focused on the concept of smart-troubleshooting to enable higher resilience and possibly self-healing in connected Cyber-Physical Systems (CPS) within the Industrial Internet of Things (IIoT), “Troubleshooting as a Service” (TaaS).
Analysis of log files to enable smart-troubleshooting in Industry 4.0: a systematic mapping study (Dec 2023) Sania Partovian, Alessio Bucaioni, Francesco Flammini, Johan Thornadtsson Journal of IEEE Access (IEEE-Access)
LogGenST: A Framework for Synthetic LogGeneration using LLMs for smart-troubleshooting Sania Partovian, Francesco Flammini, Alessio Bucaioni, Johan Thornadtsson Lecture Notes in Business Information Processing (LNBIP)
Leveraging GANs to Generate Synthetic Log Files for Smart-Troubleshooting in Industry 4.0 Sania Partovian, Francesco Flammini, Alessio Bucaioni 50th Euromicro Conference Series on Software Engineering and Advanced Applications (SEAA) (SEAA 2024)
A vision for leveraging product information and log files to enablesmart-troubleshooting of heterogeneous interconnected devices Sania Partovian, Alessio Bucaioni, Francesco Flammini, Johan Thornadtsson 5th IEEE International Conference on Human-Machine Systems (IEEE ICHMS 2025)