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Date: September 25th, 2019
Educational Seminar: Control for Power Electronics (Co-sponsored Event)



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Events on May, 2019

CASS-SCV Artificial Intelligence for Industry (AI4I) Forum – Spring 2019

Date: May 22nd, 2019

CASS-SCV Artificial Intelligence for Industry (AI4I) Forum – Spring 2019

Event sponsored and organized by:

IEEE Circuits and Systems Society (CASS)


Registration Link:

Click here to register.


Wednesday, May 22nd, 2019. 1 PM – 5 PM


1:00 – 1:30 PM Check-in / Networking & Refreshments

1:30 – 2:15 PM Prof. Kurt Keutzer (UC Berkeley)

2:15 – 3:00 PM Mr. Lingjie Xu (Alibaba)

3:30 – 4:15 PM Prof. Yung-Hsiang Lu (Purdue University)

4:15 – 5:00 PM Dr. Pradeep Dubey (Intel)

5:00 PM Adjourn


International Technological University, Main Auditorium

2711 N 1st St, San Jose, CA 95134 (between Montague & Trimble along N. 1st Street)

VT Light Rail access from downtown San Jose and Mountain View. In person attendance requested. Maximum capacity: 280. Please register to gaurantee seating.


1:30 – 2:15 PM Prof. Kurt Keutzer (UC Berkeley)

TITLE: Co-Design of Deep Neural Nets and Neural Net Accelerators for Embedded Vision Applications

ABSTRACT: Deep Learning is arguably the most rapidly evolving research area in recent years. As a result it is not surprising that the design of state-of-the-art deep neural net models proceeds without much consideration of the latest hardware targets, and the design of neural net accelerators proceeds without much consideration of the characteristics of the latest deep neural net models. Nevertheless, we show that there are significant improvements available if deep neural net models and neural net accelerators are co-designed.

2:15 – 3:00 PM Mr. Lingjue Xu (Alibaba)

TITLE: Benchmarks for Post General Purpose Computing Era

ABSTRACT: From tick-tock to process-architecture-optimization, general purpose computing is slowed down by invisible hand of economics. In the meanwhile, machine learning (ML) is driving the rise of specialized processors. The industry needs a broad benchmark suite for measuring ML hardware accelerators, as well as corresponding software frameworks and cloud platforms. In this talk, I will share stories of recent development in this field and discuss why a widely accepted benchmark suite will benefit the entire ecosystem.

3:30 – 4:15 PM Prof. Yung-Hsiang Lu (Purdue University)

TITLE: Low-Power Computer Vision: Status, Challenges, and Opportunities

ABSTRACT: Energy efficiency plays a crucial role in making computer vision successful in battery-powered systems, including drones, mobile phones and autonomous robots. Since 2015, IEEE has been organizing annual competition on low-power computer vision to identify the most energy-efficient technologies for detecting objects in images. The scores are the ratio of accuracy and energy consumption. Over the four years, the winning solutions have improved the scores by a factor of 24. The speaker will describe this competition and summarize the winning solutions, including quantization and accuracy-energy tradeoffs. Based on technology trends, the speaker will identify the challenges and opportunities in enabling energy-efficient computer vision.

4:15 – 5:00 PM Dr. Pradeep Dubey (Intel)

TITLE: AI: What Makes it Hard and Fun!

ABSTRACT: The confluence of massive data with massive compute is unprecedented. This coupled with recent algorithmic breakthroughs, we are now at the cusp of a major transformation. This transformation has the potential to disrupt a long-held balance between humans and machine where all forms of number crunching is left to computers, and most forms of decision-making is left to us humans. This transformation is spurring a virtuous cycle of compute which will impact not just how we do computing, but what computing can do for us. In this talk, I will discuss some of the application-level opportunities and system-level challenges that lie at the heart of this intersection of traditional high-performance computing with emerging data-intensive computing.

Presentation Slides:

Kurt Keutzer, ‘Co-Design of Deep Neural Nets and Neural Net Accelerators for Embedded Vision Applications’

Lingjie Xu, “Benchmarks For Post General Purpose Computing Era”

Yung-Hsiang Lu, “Low-Power Computer Vision: Status, Challenges, Opportunities”

Pradeep K Dubey, “AI: What Makes It Hard and Fun!”

NFIC-2019: Networks of the Future, Emerging Technologies for 5G and Beyond

Date: May 14th, 2019

NFIC-2019: Networks of the Future, Emerging Technologies for 5G and Beyond

Organized by IEEE-NATEA

Registration Link: here


The challenges of network connectivity and edge computing has driven research in Millimeter Waves, Small cells, MIMO, Beam-forming, Optical transport, semiconductor technologies and to help realize the 5G vision of tactile internet applications and beyond. Industry and governments are pushing to support wider & shared spectrum, massive & mission critical low latency sensitive, cloud-native, innovative mobile applications.

The globalization, immigration, energy security, punitive trade tariffs, and uncertain markets have disrupted the employment opportunities and lead to several political leaders trying to meet their national goals through protectionist policies and investing in local infrastructure for digital transformation, education & re-training in next frontiers in computation, communications & healthcare innovation.

To rein the massive costs of research and inventions, open source has become a vehicle for shared efforts to standardization for mass deployments of Infrastructure & newer Radio (NR, MEC, NSA/eNdodeB, SA/ gNodeB) and dis-aggregated Packet Core (vEPC) NFV/SDN Platforms. The DevOps, Micro Services, CI/CD and modular and agile ways to architect, design, build and deploy is the new norm. In these dynamic challenging environment “Next Frontier in Computing -2019” our annual event brings to you the Industry and academic leaders who will throw light on newer perspective how providers are redefining and deploying 5G and Edge Services, emerging Photon Cell site routers and using Semiconductor Technologies for GPU/NPUs, Data Center & Cloud services Developers and Deployers who are translating the hardware and software with AI/ML and other emerging trends in AR/VR & persistent re-configurable and programmable devices.

NFIC-2019 Speech Title and Speakers:

“5G infrastructure and key research” — Dr. Ajith Amerasekera

“Are we ready for Edge Cloud and 5G?” — Jeni Panhorst

“Edge computing for data centers” — Anand Chandrasekher

“5G Impact Beyond Technology” — Tom Tofigh

“Photonics in computing” — Prof. Jelena Vuckovic

“Content creation and consumption changes with 5G” — Amy LaMeyer

“5G is broken!!! Can it be fixed?” — Brian Zahnstecher

The Evolution of Artificial Intelligence: From the Past to the Future & Machine Learning for Veracity of Big Data

Date: May 11th, 2019

2nd annual Computer, Software, and Electrical Engineering Technology Showcase

  • These talks are jointly organized by IEEE CS and IEEE CIS Chapters
  • Third co-sponsor is IEEE SSCS Chapter for helping on publicity
  • Fourth co-sponsor is IEEE CASS Chapter for helping on publicity
  • Fifth co-sponsor is Silicon Valley Engineering Council  for helping on publicity
Time & Location:
From 10am to 11.30am on May 11th 2019 at SJSU.  

(Register here)

1) Talk title: The Evolution of Artificial Intelligence: From the Past to the Future

In this talk, I will trace the development of AI through the key inventions in AI, covering the development of machine learning, speech recognition, image understanding, deep learning and reinforcement learning. You will get a behind-the-scene view of Amazon Alexa, Apple Siri, and DeepMind’s AlphaGo. This talk will give you an understanding of core AI technologies today and the historical context behind them. Finally, I will share my view on the next big things, where jobs go, and where new products can be built.



Dr. Junling Hu is the author of a new book titled The Evolution of Artificial Intelligence.. Dr. Hu has been an AI researcher, technology leader, and educator for the last 20 years. She is a recipient of National Science Foundation Career Award. She has worked as Director of data mining at Samsung, and managed AI teams at PayPal, eBay and Bosch. She has also worked as an Assistant Professor at University of Rochester. Currently she is the CEO of AIPro Camp LLC dba, an AI education company devoted to training and education about AI. Dr. Hu received a PhD in Computer Science from University of Michigan at Ann Arbor and her research was focused on reinforcement learning. Her dissertation title was “Learning in Dynamic Non-cooperative Multiagent Systems” and led to many well-cited papers.

2) Talk Title: Machine Learning for Veracity of Big Data

Machine Learning is increasingly proving itself to be the mortar of modernization. The talk will examine how Machine Learning can be applied to the problem of veracity of Big Data, particularly, Web information. We are overwhelmingly depending on data for crucial tasks like driving as in self-driving cars, delivery as in autonomous drones and even in electing Presidents of countries, owing to the role of Online Social Networks like Twitter in these elections. Trusting technology has become inevitable. Compromising the quality of data in these circumstances can be hazardously risky. Ideally, data should be entirely truthful and accurate. However, there have been a number of instances where data was manipulated or posted fraudulently for ulterior motives, causing serious damage. Misinformation Containment is indeed a difficult task and computationally, has been proven to be NP-hard.

The Web is an important enabler of the evolving world economy and has the potential to bring more and more people into the mainstream. The Web, being humanity’s largest source of information and interaction, can serve as a conduit of humanitarian services and presents a huge opportunity to enhance the quality of life further. Unfortunately, a significant percent of the information posted on the Web is not entirely true, which substantially limits its ability to serve the needs of the humanity. this talk will go deeper into the ideas from Machine Learning to see how we can help make the World Wide Web, particularly the Social Media part of it, entirely truthful, which should ideally be an important milestone to achieve in the near future. The talk will draw from the speaker’s recent book “Big Data: Machine Learning and Other Approaches to Verifying Truthfulness”.



Dr. Vishnu S. Pendyala is the author of a new book titled Veracity of Big Data. Dr. Pendyala leads the DevOps activities at Cisco for some significant products. He is a seasoned Technical Leader with over two decades of development, porting, and DevOps experience with industry leaders like Cisco, Synopsys, Informix (now IBM), and Electronics Corporation of India Limited. He received his PhD in Computer Engineering from Santa Clara University. His dissertation title was “Evolving a Truthful Humanitarian World Wide Web”. Earlier, he received MS (Computer Engineering) degree from San Jose State University. He also received BE (Computer Science), MBA(Finance) degrees both from Osmania University, Hyderabad, India.

Open to all to attend
(Online registration is needed. If you did not register, seating is not guaranteed.)

Intelligent Ear-Level Devices for Hearing Enhancement and Health and Wellness Monitoring

Date: May 9th, 2019

IEEE SPS Distinguished Industry Speaker Talk:

Intelligent Ear-Level Devices for Hearing Enhancement and Health and Wellness Monitoring

Event Sponsored and Organized By:

IEEE SPS Chapter of Santa Clara Valley


IEEE EMBS Chapter of San Francisco

Solid-State Circuits Society(SSCS)

Circuits and Systems Society – Santa Clara Valley Chapter (CASS-SCV)

Registration Link: here.

DIS Speaker:

Tao Zhang, Ph.D., Director of Signal Processing Research Department, Starkey Hearing Technologies

(6600 Washington Ave. S., Eden Prairie, MN 55344, USA)

Location: AMD 2485 Augustine Dr, Santa Clara, CA 95054 (Google Maps)

Venue Details: Please park in parking structure close to the building on Octavius Drive. First building after passing AMD and the road does a curve to the right. Please walk around AMD building to the Highway 101 side to the visitor entrance.


6:30pm-7:00pm: Registration, Food, Networking

7:00pm-8:00pm: Talk

8:00pm-8:30pm: Q&A and Networking


FREE for IEEE members

Suggested donations to cover food and water (pay at door):

Non-IEEE: $5

Students (non-IEEE): $3

Online registration is recommended to guarantee seating

DIS Talk Abstract:

With resurgence of AI and machine learning, sensor miniaturization and increased wireless connectivity, ear-level devices are going through a major revolution transforming themselves from hearing devices into hearing enhancement and health and wellness monitoring devices. In this talk, we will present examples of such transformation in the areas of hearing enhancement, health and wellness monitoring and user experience. In the process, we will highlight how AI and machine learning, miniaturized sensors and wireless connectivity are enabling and accelerating the transformation. In addition, we will discuss practical challenges for the transformation today. Finally, we will provide an outlook on future directions and opportunities.

DIS Speaker Biography:

Tao Zhang received his B.S. degree in physics from Nanjing University, Nanjing, China in 1986, M.S. degree in electrical engineering from Peking University, Beijing, China in 1989, and Ph.D. degree in speech and hearing science from the Ohio-State University, Columbus, OH, USA in 1995. He joined the Advanced Research Department at Starkey Laboratories, Inc. as a Sr. Research Scientist in 2001, managed the DSP department from 2004 to 2008 and the Signal Processing Research Department from 2008 to 2014. Since 2014, he has been Director of the Signal Processing Research department at Starkey Hearing Technologies, a global leader in providing innovative hearing technologies. He has received many prestigious awards including Inventor of the Year Award, the Mount Rainier Best Research Team Award, the Most Valuable Idea Award, the Outstanding Technical Leadership Award and the Engineering Service Award at Starkey.

He is a senior member of IEEE and the Signal Processing Society and the Engineering in Medicine and Biology Society. He serves on the IEEE AASP Technical Committee, the industrial relationship committee and the IEEE ComSoc North America Region Board. He is an IEEE SPS Distinguished Industry Speaker and the Chair of IEEE Twin-cities Signal Processing and Communication Chapter.

His current research interests include audio, acoustic, speech signal processing and machine learning; multimodal signal processing and machine learning for hearing enhancement, health and wellness monitoring; psychoacoustics, room and ear canal acoustics; ultra-low power real-time embedded system design and device-phone-cloud ecosystem design. He has authored and coauthored 120+ presentations and publications, received 20+ approved patents and had additional 30+ patents pending.

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