CASPA 2017 Annual Conference Dinner Banquet
Oct 28, 2017


LOCATION

Santa Clara Convention Center, 5001 Great America Parkway, Santa Clara, CA 95054

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Artificial Intelligence (AI) has seen resurgence in recent years fueled by the advance in computational power, algorithms and large amount of data, which are propelled by the semiconductor chip technology. AI technology in turns creates new demand for semiconductor industry. How to accelerate machine learning at scale? What are the industrial leading hardware architecture and deep learning frameworks? What are the innovations in Distributed Machine Learning for Large-scale IoT Systems? How our industry leaders apply machine learning to autonomous drive quality and electronic design automation? What is the frontier and what are the new market segments powered by AI and Semiconductor fusion? What are the inflections points in our industry and how to address common issues collectively through supply chain? We have invited experts in both AI and semiconductor fields to discuss all the topics.


 

Startup Roadshow Agenda:

09:30 – 10:00    Registration& Networking

10:00 – 12:20    Startup Roadshow (Pitch & Demo)

 

Annual Conference Agenda:

12:00 – 13:00 Registration and Networking

13:00 – 13:30 CASPA Board of Directors Election

13:30 – 13:40 Welcome from CASPA President

13:40 – 15:50    Keynote Speeches:

Accelerating AI from the Cloud to the Edge

Wei Li, VP, Intel

Distributed Machine Learning for Large-scale IoT Systems

Rob Aitken, Fellow, ARM

Machine Learning in Advanced Automotive Quality

Guna Ponnuvel, Director, NVIDIA

Intelligent Systems for Electronic Design Automation

David White, Distinguished Eng., Cadence

Pixels, Deep Learning and Startups: the Revolution in Ubiquitous Imaging

Chris Rowen, CEO, Cognite Ventures

15:50 – 17:00 Panel Discussion: AI &Semiconductor Fusion

Moderator: Mario Morales, Program VP, IDC

Deep Learning - Powering Autonomous Driving

David Liu, Co-Founder & CEO, PlusAI

Democratizing Autonomous Driving with Affordable Cameras and AI

Jianxiong Xiao, CEO, AutoX

The XMT processor for AI

Xingzhi Wen, CEO, Pintuitive

Transforming the Semiconductor Industry with AI and Machine Learning

Jeff David, CEO, StreamMosaic

Equipment Intelligence is more than AI

Alan Berezin, Managing Director, Lam Research



Wei Li, VP,  Intel: Accelerating AI from the Cloud to the Edge

 

Abstract: Artificial Intelligence is transforming the way businesses operate and how people engage with the world. This talk will cover Intel’s AI strategy from the cloud to the edge. Today, Intel powers the cloud and data center servers, and offers the most flexible, yet performance-optimized, portfolio of AI solutions. This includes Intel® Xeon® and Intel® Xeon Phi™ processors to more workload-optimized accelerators, including FPGAs (field-programmable gate arrays) and the technology innovations acquired from Nervana. On the edge, Intel is assembling a broad set of technology options to drive AI capabilities in everything from drones, to smart factories, sports, fraud detection and autonomous driving vehicles. In addition to silicon, Intel has broad and deep software capabilities, and is actively working with the industry to enable the software ecosystem to unleash the next big wave of AI.


BIO and Photo

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Bio: Wei Li is vice president in the Software and Services Group and general manager of Machine Learning and Translation at Intel Corporation, responsible for several areas of software systems including machine learning, binary translation, and emulation. His team also works with industry and academia to enable the software ecosystem for Intel platforms, and collaborates with Intel hardware teams for designing future processor products. Since joining Intel in 1998, Li has led teams that contributed to Intel data center, client/mobile, Internet-of-things, and artificial intelligence businesses. Li obtained a Ph.D. in computer science from Cornell University on compiling for supercomputers, and completed the Executive Accelerator Program at the Stanford Graduate School of Business. He served as an associate editor for ACM Transactions on Programming Languages and Systems.


Rob Aitken, Fellow, ARM: “Distributed Machine Learning for Large-scale IoT Systems”

Abstract: The Internet of Things vision promises systems where huge numbers of sensors gather data and machine learning algorithms in the cloud process and make sense of it. While such solutions sound desirable and simple in theory, their practical implementation is complicated. In particular, there are multiple communication bottlenecks between the sensors and the cloud, as well as large amounts of unexploited compute capability along the way. This talk looks at some of the issues involved and explores promising avenues for future innovation.

Bio & Photo

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Rob Aitken is an ARM Fellow responsible for technology direction at ARM Research. He works on low power design, library architecture for advanced process nodes, technology roadmapping, and next generation memories. He has worked on 15+ Moore’s law nodes and has published over 80 technical papers, on a wide range of topics.  Dr. Aitken joined ARM as part of its acquisition of Artisan Components in 2004. Prior to Artisan, he worked at Agilent and HP.  He holds a Ph.D. from McGill University in Canada. Dr. Aitken is an IEEE Fellow, and serves on a number of conference and workshop committees.


Guna Ponnuvel, Director, NVIDIA: “Machine Learning in Advanced Automotive Quality”

Abstract: Autonomous vehicles, with their successful early programs and tremendous potential, make headline news every day and promise to dramatically change the economics of many industries. As the automobile industry is transitioning to self-driving, automotive quality requirements become even more critical. This talk gives an overview of the automotive supply chain complexity, tools and processes used to manage quality of all the components of a complex autonomous driving system and application of machine learning in test processes to achieve desired quality. The traditional OEM-supplier model will not be enough to meet the quality requirements of autonomous drive technology and need true partnerships with total transparency of unit level feedback when components fail.

Bio & Photo:

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Guna Ponnuvel is Director of Product Engineering at NVIDIA, responsible for the bring-up and qualification of chip and board products. Guna has worked on leading edge technology for 15 years, innovating many silicon process optimization, test productivity & quality improvement techniques to enable low transformation cost and high quality commercial and automotive products.Prior to joining NVIDIA, Guna was responsible for the bring -up and qualification of Conexant’s Central Office and Customer Premises Equipment chipset products. He holds a bachelor’s degree in EE from Bharathiar university, India and a master’s degree in EE from Illinois Institute of Technology, Chicago.

David White, Distinguished Engineer, Cadence: “Intelligent Systems for Electronic Design Automation”

Abstract: There is an increase in design uncertainty presented by new silicon technology and additional verification needs that contribute to an increase in potential risks. In conventional design flows, prior design and layout data and analytics are not leveraged efficiently in guiding the next design. Advances in analytics, machine learning and optimization methods are required as part of a multi-faceted solution. This talk will present an approach for using machine learning to improve design productivity while allowing for greater optimization, performance and robustness in state-of-the-art electronics development.

Bio & Photo:

David White (Sc.D. ’01) received a Doctor of Science Degree in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology.  Dr. White is currently a Senior Group Director for R&D with the Virtuoso Product Group at Cadence Design Systems.  He joined Cadence in 2006 through the acquisition of Praesagus, a software company he co-founded in 2001 and where he served as CTO. Previously he co-founded the machine learning based software company, Neurodyne and served as a Visiting Scientist at the MIT Artificial Intelligence Lab.

Dr. White was appointed to the Advisory Board for the National Science Foundation (NSF) in Washington D.C. and the MIG Advisory Board at MIT.  He was an editor and co-author of the Handbook of Intelligent Control, a text written in 1992 by leaders in the machine learning community and the NSF.  He also co-organized and chaired one of the first industry led conferences on neural networks in 1990.  He has given invited talks at the White House Office of Science and Technology Policy (OSTP) and NSF forums on neural networks and AI, as well as at IEEE, NASA, ACM and IJCNN conferences.   

Chris Rowen, CEO, Cognite Ventures: "Pixels, Deep Learning and Startups: the revolution in ubiquitous imaging”   


Abstract:  The dramatic proliferation of cameras doesn’t just change the quantity of image streams and applications, but also drives fundamental qualitative shifts on the role of imaging in technology, business and society.  This talk explores the most important changes as camera systems are designed and deployed just for computer vision, as the urban-area density of cameras sky-rockets, and as deep learning methods change the nature of insights we can extract, and as vision-inspired statistical computing supplants traditional computing models .  Deep learning, in particular, is driving a new wave of innovation and of startups built to extra much more insight from existing surveillance, monitoring, human-machine- interface, robotic and automotive streams.  The distribution of these innovators across geographies and application segments tells us a lot about how vision will change most.  As a byproduct of studying the targets for new ventures in vision, we can even derive useful lessons about the entrepreneurial success formula in the vision space.


Bio and Photo:

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Chris Rowen is a well-known Silicon Valley entrepreneur and technologist.  He created Cognite Ventures in 2016 to invest in, advise, and analyze the cognitive computing and deep learning startup arena.  He has served as CTO for Cadence’s IP Group, where he and his team develop new processor and memory for advanced applications in mobile, automotive, infrastructure, deep learning and IoT systems.  Chris joined Cadence after its acquisition of Tensilica, the company he founded to develop extensible processors. He founded and led Tensilica as CEO and CTO, to become one of the leading embedded architectures, with  more than 225 chip and system company licensees, who together have shipped more than 12 billion processor cores. Before founding Tensilica in 1997, he was VP and GM of the Design Reuse Group at Synopsys. Chris also was a pioneer in developing RISC architecture and helped found MIPS Computer Systems, where he was VP of Microprocessor Development. He holds an MSEE and PhD in electrical engineering from Stanford and a BA in physics from Harvard.  He holds about 50 US and international patents.  He was named an IEEE Fellow in 2015 for his work in development of microprocessor technology.

Panel Discussion (Moderator: Mario Morales, VP of IDC):


Mario Morales is the program vice president of IDC's enabling technologies and semiconductor research. He is responsible for in-depth analysis, evaluation of emerging markets, forecasting, and research of major semiconductor application areas such as embedded and intelligent systems, wireless, personal computing, wired communications, and consumer.

Mr. Morales is an industry analyst with over 25 years of extensive experience in managing a multinational research team of analysts, management consultants, and business development managers, Author of over 220 reports and studies in the area of semiconductors, mobile, PC, wireless, embedded, and ICT marketplace. Mr. Morales is a trusted advisor to leading high tech company executives, financial investors, and bankers on market landscape and direction, product and technology positioning, competitive benchmarking, M&A, HW and SW technology, and brand health and sustainability. His career includes past positions with NEC Electronics and Dataquest.


David Liu, Co-Founder & CEO, PlusAI: “ Deep Learning - Powering Autonomous Driving”



Abstract:  Huge progress has been made in autonomous driving over the past 30 years. As machines are extending human’s cognitive power, we are at the dawn of an autonomous driving future. Yet significant challenges lie ahead. Deep learning technologies will be at the center of addressing those challenges. Some examples are shown to demonstrate how deep learning technologies can be applied in the autonomous driving subsystems, such as perception, planning, control, and human-computer interface.


Bio:David Liu is the co-founder and CEO of PlusAI, a venture focused on building autonomous driving technology. Previously, David was the founder and CEO of RedAtoms, a top mobile gaming operator in key Asia markets. He also co-founded RMG Networks and served as CTO until its successful IPO. He started his career at Hewlett-Packard, Silicon Silicon Graphics, and later Mckinsey. Besides, David has been a fellow of the Chinese “Thousand Talents Plan” since 2012.


David holds a Ph.D. and Master of Science degree in Electrical Engineering from Stanford University.


Jianxiong Xiao, CEO, AutoX: “Democratizing Autonomous Driving with Affordable Cameras and AI”

Abstract: AutoX is striving to democratize autonomy and make autonomous driving universally accessible to everyone. With over 10 years of experience in computer vision and robotics, Professor X is working to reduce the price of entry into the autonomous driving field for several orders of magnitudes with an innovative camera-first solution -- using cameras as primary sensors. By doing so, he posits, the safety and convenience benefits of autonomy will be delivered to more people, faster. He will share how he found a company with the mission of democratizing autonomy, gather an expert team, and commercialize his passion.

Bio - Dr. Jianxiong Xiao is the founder and CEO of AutoX, a silicon valley tech startup focusing on creating full-stack A.I. software solution for self-driving vehicles. Former professor and founding director at Princeton’s Computer Vision & Robotics Lab, Xiao has over ten years of research and engineering experience in Computer Vision, Autonomous Driving, and Robotics. In particular, he is a pioneer in the fields of 3D Deep Learning, RGB-D Recognition and Mapping, Big Data, Large-scale Crowdsourcing, and Deep Learning for Robotics.


Xingzhi Wen, CEO, Pintuitive: “The XMT processor for AI”


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BIO: Xingzhi Wen, Ph.D. is the co-founder of Pintuitive, a startup company focusing on parallel computing based on XMT technology. Dr. Wen worked as Sr. Digital Design Manager at Marvell and Sr. Digital Design Engineer at NVIDA and Apple. During Ph.D study, Dr. Wen prototyped the first 64-core XMT processor in FPGA. Dr. Wen holds Ph.D from University of Maryland, College Park and MS and BS from Tsinghua University, Beijing.



Jeff David, CEO, StreamMosaic: “Transforming the Semiconductor Industry with AI and Machine Learning”


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Bio:  Jeff David is the Founder and CEO of StreamMosaic and author/co-author of 82 granted US patents.  StreamMosaic develops production-implementable AI products that improve yield and reduce costs in semiconductor manufacturing by leveraging data throughout the manufacturing and testing process.  For over 20 years, Jeff has been inventing and implementing process control systems for the world’s largest semiconductor manufacturers.  Prior to founding StreamMosaic in 2014, Jeff was at Applied Materials for 18 years.  Jeff received his M.B.A. from Indiana University Kelley School of Business, his M.S. in Interdisciplinary Engineering from Purdue University, and his B.S. in Electrical Engineering from Purdue University.


Sub-16nm device nodes and new device architectures have created unprecedented manufacturing challenges, and have put pressure on the industry to find completely new ways to keep costs down while maintaining high yield and device performance.  In order to achieve acceptable yield and performance levels with these new architectures and processes, very tight process specifications must be achieved. A large part of the problem is that individual steps involved in fabrication and testing require complex integration and can no longer be performed independently of each other.  Thus, better process control, testing and integration schemes are needed now more than ever.  Fortunately, the emergence of new machine learning and artificial intelligence (AI) technologies have presented novel and transformative ways to leverage the growing amount of test and process data collected.  By leveraging and integrating data collected pre and post-wafer sort and by employing robust and scalable machine learning algorithms tailored specifically for semiconductor manufacturing, many of these new challenges faced by the industry can be addressed in a cost-efficient manner.


Alan Berezin, MD, Lam Research: “Equipment Intelligence is much more than AI”

Alan received his BA in physics from UC Berkeley and spent several years doing software development before pursuing his Ph.D. in physics from University of Texas Austin.  He then spent 6 years at Advanced Micro Devices on yield enhancement before leaving to cofound a software analytics startup, Drillinginfo.  As CTO, he and the team grew the business to 500 person worldwide firm.  Following the sale of that business, he stayed on in a corporate strategy role until leaving to pursue investing and consulting.  Alan join the Advanced Equipment and Process Control group as a managing director in 2016 where he is focused on equipment intelligence, concept & feasibility of computational products, and software enabled products.


Dinner Banquet Agenda:

17:00 – 18:15 Registration & Networking

18:15 – 19:00 Opening with Traditional Band & Dinner

19:00 – 19:15 Retiring Board of Directors Service Recognition Awards

19:15 – 19:45 CASPA 2017-2018 Leadership Transition

19:45 – 20:15 Executive Keynote:

Founders, Builders, and New Leaders Propel the Global

Electronics Manufacturing Industry

Ajit Manocha, President and CEO, SEMI

20:15 – 20:30    2017 Student Scholarship Award

20:30 – 21:30    Prizes Drawing and Networking


Dinner Banquet Executive Keynote Speaker

 

Founders, Builders, and New Leaders Propel the Global Electronics Manufacturing Industry

                                Ajit Manocha

                                   President and CEO, SEMI

ABSTRACT

2017 is a record-breaking year.  Semiconductor sales will top $400B, semiconductor equipment sales are on track to shatter prior highs set in the year 2000.  The past progression of monolithic demand drivers has been replaced by a diversity of applications including: AR, VR, AI, cloud storage, IoT, Smart Automotive (driver assistance and autonomous), Smart Manufacturing, and Smart MedTech. These growing demand drivers and the increasing silicon (semiconductor) content in electronics is fueling what many are calling a “super cycle.”

How did we get here – and where are we headed?  The electronics manufacturing industry has grown and prospered, and SEMI has speed the time to better business results for the industry, because of founders, builders, and today’s new industry leaders.  These groundbreakers, trailblazers, and transformers continue to play roles in our industry’s future.  Similarly, geographic regions have invested to develop semiconductor and electronics manufacturing and have emerged, grown, specialized, and matured in a cycle that has moved around the globe.  China is the latest to take the high-growth spotlight, with a projected annual fab spending surpassing $11B in 2018 and potentially exceeding $18B in 2020.

While looking ahead to see where the industry is heading, it is important to highlight the roles of founders, builders, and new leaders.  To continue to connect, collaborate, and innovate at the exponential rate, our global industry needs to identify the inflections and common issues to address collectively.  There is more work to do together to simplify and streamline the electronics manufacturing supply chain to ensure continued growth and prosperity through this “super cycle” and beyond.  There has never been a more exciting time to be working in our industry.

 

 

BIOGRAPHY


Ajit Manocha is the president and CEO of SEMI. Headquartered in Milpitas, California, SEMI is the global industry association serving the electronics manufacturing supply chain. Manocha, an industry leader has over 35 years of global experience in the semiconductor industry.

 

Manocha was the former CEO at GLOBALFOUNDRIES, during which he also served as vice chairman and chairman of the Semiconductor Industry Association (SIA). Earlier, Manocha served as EVP of worldwide operations at Spansion. Prior to Spansion, Manocha was EVP and chief manufacturing officer at Philips/NXP Semiconductors. He began his career at AT&T Bell Laboratories as research scientist where he was granted several patents related to microelectronics manufacturing.

 

Additionally, Manocha has served on the President’s committees for “Advanced Manufacturing Partnerships” and the President’s Council of Advisors on Science & Technology (PCAST) during the last 4+ years.