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11 meetings

Title:
IEEE Virtual Distinguished Lecturer (VDL) Talk: "RFID for Human Activity Sensing: Challenges, Solutions and Applications"
Date:
May 2nd
5:00 PM (1.2 hours)
Location:
New York, NY
Abstract:

The IEEE ComSoc New York Chapter is organizing a series of technical seminars for the New York area IEEE members and the general public. We invite researchers and professionals to share their latest work on a variety of topics in communications and related areas. This is the fourth seminar of the series. Together with our fellow IEEE ComSoc Chapters, we have the great pleasure to invite Dr. Shiwen Mao, an IEEE Distinguished Lecturer, to give a talk on "RFID for Human Activity Sensing: Challenges, Solutions and Applications", with a ComSoc session number of 24444.

Title:
IEEE CS Webinar: IEEE Oregon Section Technical Seminar - Physical Assurance and Inspection of Electronics
Date:
April 29th
7:00 PM (1 hour)
Location:
Online Meeting
Abstract:

 

Abstract:

Globalization has made the semiconductor industry more susceptible to trust and security issues. Hardware Trojans, i.e., malicious modification to electronic systems, can violate the root of trust when the device or systems are fabricated/assembled in untrusted facilities. As the imaging and failure analysis tools excel in the resolution and capability, physical inspection based methods become more attractive in verifying such trust issues. On the contrary, such physical inspection methods are opening new capabilities for an adversary to extract sensitive information like secret keys, memory content or intellectual property (IP) compromising confidentiality and integrity. Different countermeasures have been proposed, however, there are still many unanswered questions. This talk will focus on the state of the art physical inspection/assurance methods, the existing countermeasures, related challenges to develop new countermeasures and a research roadmap for this emerging field.

 

Title:
Oregon ComSoc Speaker: Wireless Time Sensitive Network (TSN) -From Ethernet to Wi-Fi and beyond
Date:
April 29th
5:00 PM (1.5 hours)
Location:
Portland
Abstract:

Abstract: Emerging applications such as autonomous mobile robots, smart manufacturing, immersive experiences will require distributed computing across wireless and wired networks with deterministic low latency and high reliability. Time-Sensitive Networking (TSN) is emerging as a fundamental toolset, based on the IEEE 802.1 TSN standards, for enabling accurate time synchronization and timeliness across wired and wireless networks. This talk provides an overview of the evolution of TSN and challenges from extending TSN from Ethernet to Wi-Fi (802.11) and integration with 5G Rel. 16. The presentation will discuss the state of the art in TSN features over Wi-Fi and 5G, including time synchronization, bounded latency, and high reliability. The presentation will also discuss Industry ecosystem activities currently underway by standards bodies and cross-industry alliances to make wireless TSN a reality, highlighting the TSN capabilities available on wireless networks now, certification and interoperability work that remains and open research questions.


Bio: Dave Cavalcanti is Principal Engineer at Intel Corporation where he develops next-generation wireless connectivity and distributed computing technologies to enable autonomous, time-sensitive systems and applications. He received his Ph.D. in computer science and engineering in 2006 from the University of Cincinnati. He leads Intel Lab’s research on Wireless Time-Sensitive Networking (TSN) and industry activities to enable determinism in future wireless technologies, including next-generation Wi-Fi and beyond 5G systems. He is a Senior Member of the IEEE and serves as the chair of the Wireless TSN working group in the Avnu Alliance, an industry group facilitating an ecosystem of interoperable TSN devices and deterministic networking across Ethernet, Wi-Fi, and 5G technologies

 

 

 

Join us on Zoom 
https://simnet.zoom.us/j/97049675814?pwd=RU8yMlRZVHdjc3Q5NVkwZm5NUVIrUT09

Title:
IEEE SSCS Oregon Chapter April Meeting and Seminar (Virtual)
Date:
April 28th
4:30 PM (1 hour)
Location:
ONLINE (WEBEX)
Hillsboro
Abstract:

IEEE SSCS Oregon Chapter April Meeting and Seminar

Join us for a (virtual) talk from Dr. Stefano Pellerano of Intel on Wednesday, April 28. The seminar will be held from 4:30pm to 5:30pm (PDT) via a Virtual format. Please register for the meeting link and information.

 

Abstract:

In the last few years, the interests in quantum computing has increased substantially within the EE community. A significant engineering effort is required to bring the quantum computing outside the physics research labs into potential future commercialization. Beside the fabrication of reliable qubits, other challenges such as control electronics, interconnect and packaging must be solved before a fault tolerant quantum computer can be scaled to a large number of qubits. This talk will take an IC designer perspective to briefly introduce few of the basic concepts of quantum computing, focusing on some aspects of the control systems required to manipulate and read-out quantum states of qubits. It will then try to address why and how mixed-signal and RFIC design combined with large scale integration has the potential of accelerating the implementation of a fault-tolerant scalable quantum computer.

Speaker Biography:

Stefano Pellerano received the Laurea Degree (summa cum laude) and the Ph.D. degree in electronics engineering from the Politecnico di Milano, Milan, Italy, in 2000 and in 2004, respectively. During his Ph.D., his activity was focused on the design of fully integrated low-power frequency synthesizers for WLAN applications. In 2003 he has been a consultant with Agere Systems (former Bell Labs) in Allentown, PA. Since 2004 he has been with Intel Labs, in Hillsboro, OR. He is now Principal Engineer leading the Next Generation Radio Integration Lab, where he drives several research activities focused at enabling radio circuit integration in deeply-scaled CMOS technologies. His main research contributions include MIMO transceivers for WiFi, digital PLLs, high-efficient digital architectures for polar and outphasing transmitters, mm-wave radio transceiver and phased-array systems, and low-power radios. For the last few years, he has also been exploring cryogenic CMOS integrated electronics for qubit control in fault tolerant scalable quantum computers. Stefano has authored or co-authored more than 50 IEEE conference and journal papers, one book chapter and more than 15 issued patents. He served as the Technical Program Chair and General Chair for the IEEE Radio Frequency Integrated Circuit (RFIC) Symposium in 2018 and 2019 respectively and he is now part of the RFIC Executive Committee. He is currently serving as the Wireless Subcommittee Chair for the IEEE International Solid-State Circuit Conference (ISSCC).

Title:
SPS Chapter meeting: "A Single-Loop Optimization Method for Machine Learning and Signal Processing Problems with Nested Structures" by Prof. Tianyi Chen (Rensselaer Polytechnic Institute)
Date:
April 23rd
11:00 AM (1 hour)
Abstract:

The Signal Processing Society chapter at Oregon Section will host a technical seminar by Prof. Tianyi Chen (ECSE, Rensselaer Polytechnic Institute). The talk title is "A Single-Loop Optimization Method for Machine Learning and Signal Processing Problems with Nested Structures". This is a virtual event. Please register to the event with your email address. The Zoom meeting information will be sent to the email address that you enter during the registration process a day before the event. The talk will begin at 11am PST on April 23, Friday. Please see below for the abstract and the speaker bio.

Title: A Single-Loop Optimization Method for Machine Learning and Signal Processing Problems with Nested Structures

Abstract: Optimization is becoming the enabling factor of solving machine learning (ML) and signal processing (SP) problems. So far, majority of efforts have been made to scale up problems, with relatively simple structures, to the regimes of big data and large models. Stochastic, block-coordinated, decentralized, and federated algorithms are all effective means towards this end. However, many modern problems in ML and SP, such as meta learning and reinforcement learning, inherently have nested structures, where one problem builds upon the solution of others. To tackle the problems with such nested structures, I will introduce new stochastic optimization algorithms which run in a single-loop fashion and guarantee to achieve the same sample complexity as the stochastic gradient descent method for classic problems without nested structures.

Speaker bio: Tianyi Chen received the B. Eng. degree in Communication Science and Engineering from Fudan University in 2014, the M.Sc. and Ph.D degrees in Electrical and Computer Engineering (ECE) from the University of Minnesota (UMN), in 2016 and 2019, respectively. Since August 2019, he is with Department of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute as an Assistant Professor. During 2017-2018, he has been a visiting scholar at Harvard University, University of California, Los Angeles, and University of Illinois Urbana-Champaign. Dr. Chen was a recipient of the Doctoral Dissertation Fellowship at UMN, a finalist for the Best Student Paper Award at the Asilomar Conference on Signals, Systems, and Computers, and the inaugural recipient of IEEE Signal Processing Society Best PhD Dissertation Award. Dr. Chen's current research focuses on the theory and application of optimization, machine Learning, and statistical signal processing to problems emerging in data science and wireless communication networks.

Title:
Advances in Automotive Design and Test for EMC Applications
Date:
April 22nd
8:00 AM (1.5 hours)
Abstract:

Following the two presentations on Automotive EMC Design and Test topics, Rodrigo Rodriguez, Engineering Leader, EMC Team, with Tesla will moderate a LIVE Q&A session with our industry expert speakers noted below.

Mr. Rodriguez has been in the EMC field for over 18 years; he is currently the engineering leader for the EMC team at Tesla responsible for product design and validation testing of electric vehicles and energy products. Before joining Tesla, he worked for nine years as the EMC Architect in the MRI division at GE Healthcare. He also worked at Continental Automotive (formerly Siemens Automotive) starting as a Hardware Design Engineer developing body electronic modules for six years; right after that, he focused on EMC design and validation testing for automotive electronic modules for body and powertrain controllers; he was also in charge of the EMC laboratory at Continental in Huntsville, Alabama. Mr. Rodriguez holds a Master of Engineering - Electromagnetics from University of Illinois at Chicago. He is based at the Tesla facility in Fremont, California.

Title:
Turtlebot3 Burger build 03
Date:
April 20th
6:30 PM (2 hours)
Abstract:

The first part of the meeting will focus on a quick overview of “Writing a simple publisher and subscriber (C++)” at 
  https://docs.ros.org/en/foxy/Tutorials/Writing-A-Simple-Cpp-Publisher-And-Subscriber.html.
It will be used to bring all of us up to speed on ROS 2 projects and node architecture. The tutorial will also act as a nice reference for creating ROS 2 projects.

This simple project becomes the foundation for leveraging OpenCV in an image based project. We'll go over the code that modifies the subscriber to listen for “Image” topics generated by a webcam publisher. Raw images are converted to OpenCV format and a mouse listener is then used to select areas of interest. Once an area of interest is set we can do something "interesting" with the sub-image - "a task left for the student."

Title:
IEEE PES OREGON CHAPTER April 20 MEETING
Date:
April 20th
12:30 PM (1 hour)
Location:
Portland
Abstract:

Oregon Section PES Monthly meeting

We will be hearing a virtual presentation from Mr. Shawn Bethel, Wlidfire Mitigation Specialist

 

Title:
IEEE Oregon Section April VIRTUAL Meeting IF YOU DID NOT ALREADY GET THE INVITATION, REGISTER TO GET THE MEETING LINK
Date:
April 13th
6:30 PM (1.5 hours)
Location:
Portland, WA
Abstract:

All section leaders should have received the meeting invitation last week.  If you did not receive it, please register here and I will send the link at 4:30pm Tuesday April 13th.

Title:
Signal Processing Chapter meeting: "Learning Optimal Resource Allocations in Wireless Systems" by Dr. Mark Eisen (Intel Labs)
Date:
April 9th
11:00 AM (1 hour)
Abstract:

The SPS chapter of the Oregon section will have a technical meeting at 11am on April 9, Friday. Our speaker is Dr. Mark Eisen at Intel Labs (Hillsboro, OR). Dr. Eisen will give a talk with the title "Learning Optimal Resource Allocations in Wireless Systems". This meeting will be held remotely. Please join us via Zoom; you can find the Zoom information below.

Title: Learning Optimal Resource Allocations in Wireless Systems 

Abstract: The goal of this talk is to develop a learning framework for solving resource allocation problems in wireless systems. Resource allocation problems are as widespread as they are challenging to solve, in part due to the limitations in finding accurate models for complex systems. While both exact and heuristic approaches have been developed for select problems of interest, as these systems grow in complexity to support applications in Internet of Things and autonomous behavior, it becomes necessary to have a more generic solution framework. The use of statistical machine learning is a natural choice not only in its ability to develop solutions without reliance on models, but also due to the fact that a resource allocation problem takes the form of a statistical regression problem. We propose the use of machine learning models to parameterize the resource allocation problem and train the parameters using a primal-dual learning algorithm. While fully connected networks can be represent many functions, they are impractical to train for large scale systems. Due to the graph structure and permutation invariances inherent in wireless networks, we propose the use of graph convolutional neural networks to parameterize the resource allocation policies and demonstrate how the greatly facilitate the learning process. We finally apply the developed learning framework to solve a number of representative problems in wireless resource allocation.

Bio: Mark Eisen received the Ph.D in electrical engineering and Masters in Statistics from the University of Pennsylvania in 2019. Since August 2019, he has been working as a research scientist at Intel Labs in Hillsboro, OR. His research interests include machine learning, wireless communications, networked control systems, and statistical optimization. In the summer of 2013, he was a research intern with the Institute for Mathematics and its Applications at the University of Minnesota and in the summer of 2018, was a research intern at Intel Corporation. Dr. Eisen was a recipient of the Outstanding Student Presentation at the 2014 Joint Mathematics Meeting, as well as the recipient of the 2016 Penn Outstanding Undergraduate Research Mentor Award.

 

Zoom meeting information

Join Zoom Meeting
https://oregonstate.zoom.us/j/93979349243?pwd=QWlqTnRaRUd6M1crWEVEMkF2UTVuZz09

Password: 732695

Phone Dial-In Information
+1 971 247 1195 US (Portland)
+1 253 215 8782 US (Tacoma)
+1 301 715 8592 US (Washington DC)

Meeting ID: 939 7934 9243

Join by Polycom/Cisco/Other Room System
93979349243@zoomcrc.com

 

Title:
SPS Chapter meeting: "One-Bit Sigma-Delta MIMO Precoding" by Dr. Mingjie Shao (Chinese University of Hong Kong)
Date:
April 8th
7:00 PM (1 hour)
Abstract:

The Signal Processing Society chapter of the Oregon section will host a talk by Dr. Mingjie Shao (the Chinese University of Hong Kong). The talk title is "One-Bit Sigma-Delta MIMO Precoding". The talk will begin at 7pm PST on April 8, Thursday. This event will be held remotely. Please join us via Zoom (the Zoom meeting information is attached below). Please find the talk abstract and the speaker bio below.

Title: One-Bit Sigma-Delta MIMO Precoding

Abstract: Coarsely quantized multiple-input multiple-output (MIMO) signaling methods have opened up opportunities for massive MIMO implementation using cheap and power-efficient radio-frequency front-ends. One-bit massive MIMO precoding that uses one-bit digital-to-analog convertors (DACs), is of particular interest in multiuser downlink transmission; there, a major challenge lies in how to combat the quantization noise. Previous studies usually see one-bit precoding as an optimization challenge for addressing the binary signal constraint. In this talk, we present a new one-bit MIMO precoding approach via spatial sigma-delta modulation. By assuming a uniform linear array at the base station(BS), we apply the conventional temporal sigma-delta modulation in space. The quantization noise can be significantly reduced within the angle sector that the BS aims to serve. Also, the spatial sigma-delta modulation replaces the binary signal constraints by simple signal amplitude constraints. Leveraging on the above merits, an amplitude-constrained zero-forcing (ZF) scheme is proposed. Analysis reveals that the very large number of antennas in massive MIMO provides favorable operating conditions for the sigma-delta ZF precoding.

Biography: Mingjie SHAO is a Research Associate at the Department of Electronic Engineering, the Chinese University of Hong Kong. He received his PhD in Electronic Engineering from the Chinese University of Hong Kong. His research interest is in signal processing and optimization for 5G physical-layer transmission, model-based deep learning and data mining. He was a recipient of Hong Kong PhD Fellowship Scheme (HKPFS).

Zoom meeting information

Join Zoom Meeting
https://oregonstate.zoom.us/j/97287534791?pwd=Q3FIYVh0ZDlaTzhzOCtNVmNUMnJ6UT09

Password: 201308

Phone Dial-In Information
+1 971 247 1195 US (Portland)
+1 253 215 8782 US (Tacoma)
+1 301 715 8592 US (Washington DC)

Meeting ID: 972 8753 4791

Join by Polycom/Cisco/Other Room System
97287534791@zoomcrc.com

 

11 meetings. Generated Friday, May 7 2021, at 5:54:33 PM. All times America/Los_Angeles