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.

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

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.

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."

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.

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

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