Andrea Bonetti of Sony: AI for Chip Design

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Event details

Date 04.11.2025
Hour 11:1514:00
Speaker Andrea Bonetti of Sony AI

Andrea Bonetti received a Master’s degree in Electronic Engineering from Politecnico di Milano, Italy, in 2012. In 2011, he visited the Bio Engineering Laboratory (BEL) at ETH Zurich, Switzerland. From 2012 to 2014, he worked as an Analog Design Engineer at AMS AG, Switzerland, focusing on the development of audio interfaces with MEMS sensors. He obtained a Ph.D. degree from EPFL, Switzerland, in 2019, under the supervision of Prof. Andreas Burg on the energy/quality trade-offs in digital integrated circuits. In 2016, he visited the Circuits Research Laboratory at Intel Labs, USA. From 2019 to 2023, he worked as a Senior R&D Engineer at CSEM, Switzerland, in the System-on-Chip group. Since 2023, he has been a Staff Research Scientist at Sony AI, Switzerland, where he leads a team of researchers on AI for analog circuit design.
Location
Category Conferences - Seminars
Event Language English
An Industrial Perspective on Gaining a Competitive Edge Through Automation

The growing complexity of modern chips and the pressure to maintain a competitive edge in industry are pushing traditional electronic design automation (EDA) tools to their limits, increasing the need for more customizable and scalable design methodologies. As the demand for more performant and specialized hardware keeps rising on the semiconductor market, artificial intelligence (AI) is emerging as a transformative force in chip design. This talk explores how AI can optimize key processes in the design of analog circuits and digital systems, offering a perspective from industry.

Topics include:

1) trends in AI for analog design, from simulator surrogates to generative AI for layout
2) LLMs for RTL coding and AI for efficient verification of digital systems
3) an industrial perspective on the in-house development of AI automation tools

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Practical information

  • General public
  • Free

Contact

  • Valerie Locca

Tags

generative AI LLMs for RTL coding automation

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