Keynote Speakers

Keynote Speaker 1: Professor Muhammad Mustafa Hussain

Keynote Topic: Anomalous Mechanical Deformation – New Variable in Reliability for Flexible and Stretchable CMOS Electronics
We are embarking on a future where ubiquitous electronics are deployable anywhere and seamlessly connectivity will be a reality. One of the key aspects of such electronics will be physical flexibility and stretchability. Since conventional complementary metal oxide semiconductor (CMOS) electronics are physically rigid, being physically flexible and stretchable make them subjected to uncertain electrical performance and reliability due to anomalous mechanical deformations. In this talk, therefore I will be sharing some of my perspectives and learnings on such events as they offer new dimension and insights to design reliable physically flexible and stretchable CMOS electronic devices for the future.

Bio: Mustafa (PhD, ECE, UT Austin, Dec 2005) is a Professor of EECS, UC Berkeley. He was a Founding Professor of Electrical and Computer Engineering, KAUST from 2009 to 2020. He was Program Manager in SEMATECH (2008-2009) and Process Integration Lead for 22 nm node FinFET CMOS in Texas Instruments (2006-2008). His research is focused on futuristic electronics which has received support from DARPA, Boeing, Lockheed Martin, GSK-Novartis, Saudi ARAMCO and SABIC. He has authored 450+ research papers and patents. He is a Fellow of IEEE, American Physical Society (APS) and Institute of Physics (UK), a distinguished lecturer of IEEE Electron Devices Society, and an Editor of IEEE T-ED. His research has been extensively highlighted by international media (CNN, Fox News, MSNBC, Washington Post, WSJ, National Geographic, Forbes, IEEE Spectrum, etc.) including being featured by Scientific American as one of the top 10 world changing ideas in 2014. He has received more than 45 international awards including Best Innovation Award in CES 2020, Edison Award 2020, UT Austin Outstanding Young Alumni Award 2015, IEEE Outstanding Individual Achievement Award 2016, etc. He is also the host of popular IEEE EDS Podcast Series with EDS Luminaries.

Keynote Speaker 2: Noah Lassar

Keynote Topic: Reliability Insights from 25 Million Fully Autonomous Miles
The Waymo Driver, now in its fifth generation, has been gaining experience over more than 10 years and 25 million fully autonomous miles. In this talk, you will learn how the program started, how we progressed with each generation of technology, and how we were able to launch Waymo One, our ride-hailing service that’s currently offering fully autonomous rides in the East Valley of Phoenix, Arizona. Operating a fully autonomous ride hailing service comes with plenty of unique reliability challenges, from ensuring we have reliable components, to ensuring that our fleet provides our customers with reliable and safe vehicles 24/7. To overcome these challenges, Waymo employs an exhaustive approach to reliability assurance at the material, component, subsystem, system, and fleet level.

Bio: Noah Lassar is the Head of Reliability for Waymo, formerly known as the Google’s Self Driving Car division. Prior to joining Google and Waymo, Noah was the Manager of Reliability at Tesla Motors, where he developed and executed the reliability program for Tesla’s 2013 Model S –voted Motortrend Car of the Year and recipient of a good long-term reliability rating from Consumer Reports. Noah received his Master’s degree in Mechanical Engineering from Stanford University in 2004 with an emphasis on micro electro-mechanical systems (MEMS). When Noah is not working on reliability challenges, he enjoys exploring the world with his wife and two children

Keynote Speaker 3: Professor Aaron Thean

Keynote Topic: What’s wrong with my chip? – Dr. AI, can you please diagnose?
Integral to the success of the semiconductor industry in keeping up with Moore’s law is the importance of failure analysis. However, locating defects among tens of billions of transistors packed in the tiny modern microchip is not a trivial task. Not only has the process technology to achieve such high integration of devices evolved to become astoundingly sophisticated, debugging for defects in these chips has also become remarkably complex. In this talk, we review the growing interest in the use of Machine Learning (ML) in chip design and diagnostics. This may not only accelerate the time-to-market for new chips but also the development of next-generation chips in the face of escalating process and design complexities needed to sustain the technology evolution. We will discuss some of our approach and work on developing ML-guided modeling and defect localization in in scaled devices for sub-5nm technology nodes and encouraging results to scale this to larger circuits and systems level in the near future.

Bio: Aaron Thean is a Professor of Electrical and Computer Engineering at the National University of Singapore (NUS). He currently the Dean of NUS Engineering. In addition, he holds several technical leadership responsibilities at the University; which includes Director of NUS-HiFES research program and A*Star SIMTech-NUS Joint Lab on Hybrid Flexible Electronics. From 2016-2018, he had also served under the Deputy President of Research and Technology of NUS as the Director of Industry Engagement & Partnerships. Prior to NUS, Aaron Thean was the Vice President of Logic Technologies at IMEC. Working with Semiconductor Industry leaders like Intel, TSMC, Samsung, Globalfoundries, Apple, and Sony, he directed the research and development of next-generation semiconductor technologies and emerging nano-device architectures. Prior to joining IMEC in 2011, he was with Qualcomm’s CDMA technologies in San Diego, California. Aaron and his group worked on Qualcomm’s 20nm and 16nm mobile System-On-Chip technologies. From 2007 to 2009, Aaron was the Device Manager at IBM, where he led an eight-company process technology team to develop the 28-nm and 32-nm low-power bulk CMOS technology at IBM East Fishkill, New York, from research to risk production. Before IBM, Aaron was a senior scientist at Freescale Semiconductor (and Motorola) where he performed research on many novel devices. Aaron graduated from University of Illinois at Champaign-Urbana, USA, where he received his B.Sc. (Highest Honors), M.Sc., and Ph.D. degrees in Electrical Engineering (Edmund J. James Scholar). He has published over 300 technical papers and holds more than 50 US patents. Aaron was recognized as Singapore’s National Research Foundation’s Returning Singapore Scientist.