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SUMMARY:AI-Enabled RFIC Design Beyond Human Intuition | Webinars for Young Excellence
DESCRIPTION:Abstract: Traditionally\, chip-scale RF system design has been in the domain of the expert\, dominated by thumb rules and trial-and-error techniques. Designing these ICs\, which form the bedrock of wireless networks\, is complex\, time-consuming\, requires years of expertise\, and is therefore very expensive. Historically\, the design process for RF ICs has relied on intuition-based approaches with standard templates that are subsequently optimized\, time-consuming parameter sweeps\, or ad hoc population-based metaheuristic optimization methods. There is no reason to believe that this approach is optimal in any sense. This talk will discuss how inverse design with AI-based approaches can open a new design space and enable rapid on-demand design. It will discuss deep-learning-based modeling and generative AI approaches that are transferable across process design technologies\, for inverse design and automated synthesis of mmWave/sub-THz circuits and antennas. \nRegister now: https://ieee.webex.com/weblink/register/r2ed398e9053b2933e1173fd441de4fc7 \nBio:  Dr. Kaushik Sengupta is an IEEE Fellow and currently Professor in the Department of Electrical and Computer Engineering at Princeton University. He received a B.Tech/M.Tech (dual degree) in Electronics and Electrical Communication Eng. from the Indian Institute of Technology\, Kharagpur\, in 2007\, an M.S. in Electrical Engineering from Caltech in 2008\, and a Ph.D. in Electrical Engineering from Caltech in 2012. His research interests include novel chip-scale architectures for intelligent sensing and communication for a wide range of emerging applications.  Dr. Sengupta is an IEEE Fellow. He received the DARPA Young Faculty Award in 2018\, the Bell Labs Prize in 2017\, the Young Investigator Program Award from the Office of Naval Research in 2017\, the Prime Minister Gold Medal Award from IIT Kharagpur in 2007\, the Charles Wilts Prize at Caltech for the best Electrical Engineering Ph.D. thesis in 2013\, and the inaugural Young Alumni Achievement Award from IIT Kharagpur in 2018. He served as a Distinguished Lecturer for the IEEE Solid-State Circuits Society from 2019 to 2020 and for the IEEE Microwave Theory and Technology Society from 2021 to 2023. He is a recipient of the 2021 IEEE Microwave Theory and Technology Outstanding Young Engineer Award and the 2022 IEEE Solid-state Circuits New Frontier Award. He received the IEEE Microwave Prize in 2015\, several best paper awards\, including IEEE IMS (2020\, 2021\, 2022\, 2025)\, RFIC (2012)\, and the Best Paper of the Year award from IEEE Journal on Solid-State Circuits in 2023 for the first deep-learning-enabled RFIC design.
URL:https://sscs.ieee.org/event/ai-enabled-rfic-design-beyond-human-intuition/
LOCATION:Online
CATEGORIES:Webinars for Young Excellence
ORGANIZER;CN="SSCS Young Professionals":MAILTO:d.tadros@ieee.org
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LAST-MODIFIED:20260403T235456Z
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SUMMARY:Ideas for Extreme Energy Efficiency for Analog Circuits | SSCS April Technical Webinar
DESCRIPTION:Abstract: With emerging trends such as machine learning\, the internet of everything\, brain–machine interfaces\, autonomous driving\, 6G communications\, and quantum computing\, circuit designers are increasingly challenged to achieve drastic improvements in accuracy\, speed\, and power efficiency. \nYet\, as CMOS circuit designs have matured over the past five decades\, we often find ourselves constrained by well-established topologies and methodologies\, making it difficult to realize substantial performance gains. In this webinar\, I will introduce several recent ideas that have demonstrated significant improvements in energy efficiency for analog and mixed-signal circuits such as amplifiers\, sensor interfaces\, oscillators\, power converters\, data converters\, and phase-locked loops. \nRegister here: https://ieee.webex.com/weblink/register/r9c6f25f2ff6975676e1abed61556be60 \nBiography:  Taekwang Jang received his B.S. and M.S. in electrical engineering from KAIST\, Korea\, in 2006 and 2008\, respectively. From 2008 to 2013\, he worked at Samsung Electronics Company Ltd. In 2017\, he received his Ph.D. from the University of Michigan and worked as a post-doctoral research fellow at the same institution. In 2018\, he joined ETH Zürich and is currently working as an associate professor\, leading the Energy-Efficient Circuits and Intelligent Systems group. \nHe focuses on circuits and systems for highly energy-constrained applications such as wireless sensors and biomedical interfaces. He holds 15 patents and has co-authored more than 100 peer-reviewed conferences and journal articles. He is the recipient of the 2024 IEEE Solid-State Circuits Society New Frontier Award\, the IEEE ISSCC 2021 and 2022 Jan Van Vessem Award for Outstanding European Paper\, the IEEE ISSCC 2022 Outstanding Forum Speaker Award\, and the 2009 IEEE CAS Guillemin-Cauer Best Paper Award. Since 2022\, he has been a TPC member of the IEEE International Solid-State Circuits Conference and the IEEE Asian Solid-State Circuits Conference. Since 2023\, he has served as an Associate Editor for the Journal of Solid-State Circuits and was appointed a Distinguished Lecturer for the Solid-State Circuits Society in 2024-2025.
URL:https://sscs.ieee.org/event/ideas-for-extreme-energy-efficiency-for-analog-circuits-sscs-april-technical-webinar/
LOCATION:Online
CATEGORIES:Technical Webinars
ORGANIZER;CN="SSCS Technical Webinars":MAILTO:d.marinese@ieee.org
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