Who will design tomorrow’s analog integrated circuits: humans or AI-based synthesis?
Analog/mixed-signal integrated circuits are key in applications where electronics interface with the physical world. The design of analog circuits, however, is time consuming and prone to errors, often requiring multiple redesign cycles. The rebirth of AI and machine learning, and the recent rise of generative AI methods, on the other hand, create a whole new spectrum of techniques to automate this process. This invited talk will explore the high potential of using advanced machine learning (ML) techniques to automatically synthesize and lay out analog integrated circuits. What is hype and what will be feasible? Will we still need analog designers in the future and how will they operate?
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Georges Gielen
Who will design tomorrow’s analog integrated circuits: humans or AI-based synthesis?
Analog/mixed-signal integrated circuits are key in applications where electronics interface with the physical world. The design of analog circuits, however, is time consuming and prone to errors, often requiring multiple redesign cycles. The rebirth of AI and machine learning, and the recent rise of generative AI methods, on the other hand, create a whole new spectrum of techniques to automate this process. This invited talk will explore the high potential of using advanced machine learning (ML) techniques to automatically synthesize and lay out analog integrated circuits. What is hype and what will be feasible? Will we still need analog designers in the future and how will they operate?
Biography:
Georges G.E. Gielen is a Full Professor at KU Leuven and a leading expert in analog and mixed-signal integrated circuits, with major contributions in CAD tools and design automation. He previously served as Vice-Rector and Chair of Electrical Engineering at KU Leuven, has been a visiting professor at UC Berkeley and Stanford, and has authored 10 books and more than 700 publications. He is an IEEE Fellow and recipient of several major honors, including the IEEE CAS Mac Van Valkenburg Award, the IEEE CAS Charles Desoer Award, and the EDAA Achievement Award. His talks focus on two major themes: the future of analog IC design using AI-based synthesis and machine learning, and the design of analog functions in a highly digital way to reduce cost, power, and area in applications such as automotive and biomedical systems.
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Address:Department of Electrical Engineering (ESAT) at KU ,