Mehdi Ghrabli

Mehdi Ghrabli

3rd year PhD student in machine learning

Talks and presentations

Combining machine learning with finite element simulations for fast computation in power module failure Analysis due to wire bond degradation

March 18, 2025

Talk, Arts et Métiers – ENSAM (Paris Campus), Paris, France

This talk took place at the 2025 Digital Twins in Engineering & Artificial Intelligence and Computational Methods in Applied Science confernece (DTE - AICOMAS 2025), it presented how machine learning can be used to create surrogate models for finite element simulations to reduce computational time. This work was carreid out to enable advanced frameworks for remaining useful life estimation.

Physics-informed Markov chains for remaining useful life prediction of wire bonds in power electronic modules

September 24, 2024

Poster, Paganini Conference Center, Parma, Italy

This poster was presented during the 35th European Symposium on Reliability of Electron Devices, Failure Physics and Analysis (ESREF 2024). Throught this poster, we show how kernel density estimation can be utilised as a probability density estimator, to be utilised in a Markov-Chain based sampling scheme. This sampling scheme allows us to capture the dynamic responsible for the power electronic modules’ failure, using experimental data of tests to failure, combined with numerical simulations used to generate mechanical features.

Hybrid modeling for remaining useful life prediction in power module prognosis

April 08, 2024

Talk, Four Points by Sheraton Catania Hotel & Conference Center, Aci Castello, Catania, Italy

This work was presented during the 2024 25th International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE). Its main purpose is to highlight how a physics-based model (Paris’ law) and a data-driven model (adaptive polynomial regression) can be combined to obtain a hybrid model that benefits from both model types’ strenghts.