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Doing EDA in Disruptive Times: Reflections on Analog and AI

Endowed Lecture Seminar

Location: EER 1.518
Rob A. Rutenbar
Senior Vice Chancellor for Research, Distinguished Professor of
ECE and CS, University of Pittsburgh


In this talk, I’m going to try to connect my experience working for several decades on electronic design automation (EDA, aka VLSI CAD) and analog, with the recent revolution in AI.  Analog is a particularly interesting subset of the broader chips and semiconductors landscape, as it has a formidable reputation for difficulty, and reliance on “seen patterns” in circuits as one explanation for how human experts do successful design. As it turns out, combinatorial algorithms are also pretty good at doing analog design.  But I’m also going to argue that the intersection of analog and AI is a fruitful one, specifically because of this “pattern dependency” angle.  I’m going to use three chip designs I’ve been part of to illustrate these ideas.  I’ll close with an overview of my Coursera MOOCs on VLSI CAD, which have now been operating for ten years, with 100,000+ registered students planet-wide, to talk about where we might be going next, as the world is pivoting back toward regarding chips and semiconductors as key strategic assets. 


Rob A. Rutenbar is Senior Vice Chancellor for Research at the University of Pittsburgh, where he has responsibility for Pitt’s research and innovation infrastructure. He is also Distinguished Professor of CS and of ECE. From 2010 to 2017, he was Head of Computer Science at the University of Illinois at Urbana-Champaign. He received the Ph.D. from the University of Michigan in 1984, and spent the next 25 years at Carnegie Mellon University, where he held the Jatras Chair in Engineering. 

His research focuses on tools for analog integrated circuits, and hardware architectures for AI. He has founded two successful venture-backed startups:  Neolinear (acquired by Cadence in 2004) and Voci Technologies (acquired by Medallia in 2020). He has received numerous awards for his work, including the 2017 Phil Kaufman Award from the EDA community and IEEE, and the 2021 ACM SIGDA Pioneering Achievement Award. He has co-chaired the CISE Advisory Committee for the National Science Foundation and served on multiple US National Academies study panels. His work has been featured in venues ranging from IEEE Spectrum to the Economist.

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