SystemX Alliance Newsletter - September 2024
Introducing SystemX Executive Director: Ivo Bolsens
It becomes extremely difficult and expensive to scale feature dimensions of semiconductor components as Moore’s Law is slowing down. Traditional industry roadmaps are facing severe cost, power, and speed roadblocks. At the same time, future systems that form the foundation of Artificial Intelligence, autonomous driving, and wireless communication are requesting an exponential demand in compute and data processing.
To overcome these roadmap challenges, multi-disciplinary research is required that feeds the semiconductor ecosystem and forms the foundation of an ambient intelligent environment that monitors our health, guarantees our safety, and improves our efficiency.
SystemX is one of the largest affiliate programs in Stanford that brings together researchers covering the full solution stack, combining not only knowledge in semiconductor technology but also in AI based applications, software, architectures, heterogeneous integration, as well as materials science and power management. Faculty members associated with SystemX are found across Stanford’s School of Engineering.
The unique strength of SystemX lies also in its affiliation between academia and industry. It’s a dynamic ecosystem where academia and industry join forces to create a vision and to drive technological advancements to enhance productivity and competitiveness for both academia and industry partners.
During its annual Fall Conference on November 12-14 at the Stanford campus, the SystemX Alliance brings together experts, researchers, and industry professionals to discuss topics related to the latest advancements of robotics, system design, design productivity, computing for AI, as well as new energy solutions, new materials research, and heterogeneous system-in-package integration.
This multi-disciplinary research also provides rich educational opportunities and produces world-class research and PhD graduates who learn to bridge gaps between fields, preparing them for real-world challenges.
In summary, the intricate nature of semiconductor technology and the demands of modern applications necessitate collaboration across disciplines. Whether it’s designing or programming more efficient chips or exploring new materials and chip packaging technology, multi-disciplinary research is the key to advancing semiconductor technology and System-on-Chip or System-in-Package design.
I am excited to join the leadership team of Stanford's SystemX Alliance because it allows me to be at the forefront of technology advancements that can shape the future of semiconductor industry and collaborate with brilliant minds in the industry and academia to perhaps make a difference.
Bio: Ivo Bolsens retired from AMD as Senior Vice-President Corporate Research and Advanced Development. At AMD, he managed advanced hardware and software technology development, including future architectures and software stacks to enable emerging opportunities in the fields of AI and embedded computing. He was also responsible for driving the university partnerships to create a thriving global ecosystem for AMD technology in academia.
He joined AMD in 2022, as part of the Xilinx acquisition. At Xilinx, he served as the Chief Technology Officer in charge of corporate research, responsible for all semiconductor hardware and software advanced development. He joined Xilinx in 2001 from the Interuniversity Microelectronics Centre (IMEC), an international research center based in Belgium. At IMEC he was vice president leading the R&D of digital signal processing hardware and software. During his tenure at IMEC, he spun-out several successful startups in the field of SOC design tools and wireless systems.
He serves on the advisory boards of IMEC, the Engineering Departments of San Jose State University and Santa Clara University, and the Department of Electrical Engineering and Computer Sciences at UC Berkeley.
He received his Master’s degree and PhD degree (EE) from the KU Leuven university in Belgium.
SystemX Alliance 2024 Fall Conference
November 12-14, 2024
Li Ka Shing Center | Stanford University
The 2024 SystemX Fall Conference will be held on November 12-14, 2024 at Li Ka Shing Center at Stanford University. Our faculty and students will be presenting research funded by you, our members. More details and further information to come.
We hope you will join us!
Please check back on this page for any updates:
SystemX 2024 Fall Conference event page
EE 310: Autumn Quarter 2024
Begins September 26th
systemx.stanford.edu/events?seminar=
During the academic year, SystemX holds a weekly seminar every Thursday from 4:30-5:30pm. The seminar series draws upon distinguished invited speakers from both industry and academia who are involved at all levels of the technology stack and with the emerging applications that they enable.
To be notified of upcoming seminars and receive Zoom information, make sure to subscribe to the SystemX Seminar mailing list.
- 9/26 Ivo Bolsens (Stanford) - AI Architectures for Edge and Cloud
- 10/3 Chris Dick (NVIDIA) - Intersection of machine learning and 6G wireless systems
- 10/10 Gordon Brebner (AMD) - Scale-out networking for AI datacenters
- 10/17 Fadi Alsaleem (University of Nebraska-Lincoln) - Bio-inspired edge AI
- 10/24 Prith Banerjee (Ansys) - AI driven digital twin
- 10/31 Pete Shadbolt (PsiQuantum) - Silicon Photonic Quantum Computing
- 11/7 Rajeev Jain (Qualcomm) - Low-power architectures for always-on sensing
- 11/21 Jan Rabaey (IMEC) - Brains and Computers
- 12/5 DJ Seo (Neuralink) - Interfacing with the brain
To watch recordings of previous seminars, visit: systemx.stanford.edu/events?seminar= (NOTE: you must be logged in to the SystemX website to view links for recordings and slides)
Students & Faculty Awards/Recognitions
- Prof. Mark R. Cutkosky won the 2024 Pioneer in Robotics and Automation Award "for contributions to Robot Design: from Bioinspiration to Biounderstanding"
- Prof. John Cioffi was elected as a Corresponding Fellow of the Royal Society of Edinburgh (RSE)
- Prof. Shanhui Fan was elected into the National Academy of Engineering (NAE)
- Prof. Clark Barrett won the 2024 CAV Award
- Prof. Clark Barrett and co-authors Cesare Tinelli, Haniel Barbosa, Aina Niemetz, Mathias Preiner, Andrew Rynolds, and Yoni Zohar won the Distinguished Tutorial Award at the 2024 International Symposium on Formal Methods for the paper "Satisfiability Modulo Theories: A Beginner's Tutorial"
- Prof. Priyanka Raina received the 2024 DARPA Young Faculty Award
- Sai Thatipamula (PhD student, Prof. Simona Onori group) received the Chevron Energy Fellowship 2024
- Dr. Koosha Nassiri Nazif (Postdoc, Prof. Eric Pop group) and Alex Shearer (PhD student, Prof. Stacey Bent group) have been named Breakthrough Energy Fellows - "The Fellows program is designed to tackle early-stage barriers to climate technology innovation, accelerating discovery and increasing the number of projects and companies working toward commercialization"
- Emi Zeger (Prof. Mert Pilanci group & Prof. Nick Bambos group) won Best Paper Award at the IEEE International Conference on Communications
- Dr. Justin Kruger (Postdoc, Prof. Simone D'Amico group) won the ION Parkinson Award and AA Department's Bellhaus Prize
- Prof. Simone D'Amico won the AIAA Stanford Outstanding Advisor Award in Aero/Astro presented by the AIAA Stanford Student Chapter
- Prof. Simone D'Amico also won the 2024 Barry Carlton Award for the most impactful paper published in T-AES four years prior to the award conferral.
- Rohan Sinha, Amine Elhafsi, Christopher Agia, Matthew Foutter, Edward Schmerling, and Prof. Marco Pavone received the Best Paper Award at the Robotics: Science and Systems Conference for the paper "Real-Time Anomaly Detection and Reactive Planning with Large Language Models"
- Dr. Mohammad Rahmani Fadiheh (Prof. Subhasish Mitra group), Alex Wezel, Johannes Müller (PhD student), Jörg Bormann, Sayak Ray, Jason M. Fung, Prof. Subhasish Mitra, Dominik Stoffel, and Wolfgang Kunz have been selected as a Top Picks in Hardware Security Paper for their paper "An Exhaustive Approach to Detecting Transient Execution Side Channels in RTL Designs of Processors"