Danilo Pau is technical director in the STMicroelectronics EdgeAI organization in System research and applications. He is certified as full professor ASN09/E3 on Electrical and electronic engineering and measurements by the higher italian educational system. He was awarded on 2025 on IEEE Distinguished Industry Lecturer by IEEE Italy Section. Moreover, he is a Member of the Global Governance and AI Safety Committee of the National Academy of Artificial Intelligence (NAAI) as well as Members of the Scientific Committee for the term 2026-2027 IEEE SPS Italy Chapter. Danilo is chairing the Generative EdgeAI working group in EdgeAI Foundation, the largest EdgeAI community at worldwide level.
To enhance the reliability of power electronics, deep EdgeAI is becoming an essential approach. One challenge is to scale AI massively to achieve a full distributed deployment, ideally into the power electronics itself. Therefore, a lightweight machine learning approach for estimating the Remaining Useful Life of IGBT and Silicon Carbide transistors is a useful contribution. By leveraging Radial Basis Function networks, we achieve state-of-the-art accuracy with a fraction of the computational cost. Our method is fully deployable on ultra-low memory DSPs, supporting on-chip learning and inference. This breakthrough would allow AI integrated in power transistors to move beyond simple switching, incorporating unprecedented, embedded intelligence and real-time diagnostic capabilities within a single package.