Bio :

Fabio is STMicroelectronics’ President, Quality, Manufacturing, and Technology and has held this position since July 2023. He was responsible for the company’s Back-End Manufacturing & Technology organization since 2016 and also led the Company’s Testing Council, alongside its manufacturing strategy in Asia and efforts in System-in-Package technology. Fabio is a member of ST’s Executive Committee.
Fabio joined SGS Microelettronica (now ST) R&D in 1984. He became R&D Director of Operations in 1989 and became Automotive BU Director in 1996. After two years as President and CEO of Semitool, he rejoined ST in 2000 as Group VP responsible for memory products including the RAM/PSRAM and Automotive Flash. In 2005, Fabio was appointed CEO of ST Incard, an ST smart-card subsidiary. In 2008-2010, he served as VP and Supply Chain General Manager at ST’s memory JV with Intel. In 2011, Fabio was appointed ST’s Executive Vice President, Product Quality Excellence.
Fabio has authored several technical and managerial papers and holds multiple international patents. He serves as Chairman of STS, ST's manufacturing JV in China. Fabio was born in Bergamo, Italy, in 1959. He is a Doctor in Physics from the University of Milan.

Abstract :

Since its inception in 1958, semiconductor technology has undergone rapid growth and innovation, positioning itself as one of the most dynamic segments in technological advancement. Following Moore's Law on technology evolution, and then transitioning to "More than Moore" approaches, the technology has progressed towards SoC and SiP architectures, ultimately leading to heterogeneous integration and chiplet technologies. New materials such as SiC and GaN have also been introduced, complementing Silicon, which still remains indisputably the main actor.Alongside these materials, new manufacturing techniques including SOI, W2W bonding, PLP, Fan-In-Fan-Out, DCI, PCM, FD-SOI, and II-VI quantum dots have emerged. The advancement of semiconductor technology moved hand in hand with increasing in volumes, data processing capabilities, and automation, paving the way for Edge AI applications that leverage deep learning and ML algos.
To sustain complexity and innovation, we implement edge-to-edge technology governance with integrated planning, data-driven decisions, and multidimensional organizational structures. Specific examples will clarify these concepts.