Previous 30 days30 days60 days90 days | Short FormatLong Format

using https://events.vtools.ieee.org/meetings/xml/0/30/asc/6/OREGON

46782 bytes

fixing date 2024-03-01 11:00:00 US/Pacific

fixing date 2024-03-01 12:00:00 US/Pacific

6 meetings

Title:
SusTech Talk Feb. 2024 – Nurturing Sustainability through Ubiquitous Computing
Date:
February 27th
6:00 PM (1 hour)
Abstract:

SusTech is hosting talks on Sustainability topics leading up to the 2024 conference in April.

"Harmony in the Digital Ecosystem: Nurturing Sustainability through Ubiquitous Computing"

with Anandi Giridharan, Principal Research Scientist,  ECE (Department of Electrical Communication Engineering),  Indian Institute of Science, Bengaluru, Karnataka, India

Date/Time:

  • Tuesday, 27-February-2024, 9-10 pm US Eastern, 6-7 pm US Pacific;
  • Wednesday, 28-February-2024,  7:30-8:30 am India

 

Title:
IEEE CS Webinar: IEEE Oregon Section Technical Seminar - Meltdown trilogy: Exploiting Microarchitectural Flaws to Leak Data Across Security Boundaries
Date:
February 29th
6:00 PM (1 hour)
Abstract:

We hope to have you for another interesting talk by one of the experts that we invite from academia, industry, and government.   

* As this online event is free and open to non-IEEE members, please feel free to share it with your colleagues, students, classmates, etc.

* For the abstract and biography of the speaker, please refer to the speakers section below.

* Please note that you will receive a registration confirmation email after you register for the event and you will receive a separate email containing the invite to the meeting later. You can add the link to the meeting invite to your calendar manually as the calendar invite does not get updated automatically.  

Title:
IEEE SSCS Oregon Chapter March Meeting and Seminar (Hybrid)
Date:
March 1st
11:00 AM (1 hour)
Location:
Jones Farm Conference Center
Hillsboro
Abstract:

IEEE SSCS Oregon Chapter March Meeting and Seminar

Join us for a talk from SSCS Distinguished Lecturer Prof. Zhengya Zhang from the University of Michigan, Ann Arbor, on Friday, March 1st, 2024. The seminar will be held from 11:00am to 12:00pm (PST) via a Hybrid format. Please register for the meeting link and information.

 

Topic:

ML Hardware Design for Efficiency, Flexibility and Scalability

 

Abstract:

Machine learning (ML) is the driving application of the next-generation computational hardware. How to design ML hardware to achieve a high performance, efficiency, and flexibility to support fast growing ML workloads is a key challenge. Besides dataflow-optimized systolic arrays and single instruction, multiple data (SIMD) engines, efficient ML accelerators have been designed to take advantage of static and dynamic data sparsity. To accommodate the fast-evolving ML workloads, matrix engines can be integrated with an FPGA to provide the efficiency of kernel computation and the flexibility of control. To support the increasing ML model complexity, modular chiplets can be tiled on a 2.5D interposer and stacked in a 3D package. We envision that a combination of these techniques will be required to address the needs of future ML applications.

 

Speaker Biography:

Zhengya Zhang received the B.A.Sc. degree from the University of Waterloo in 2003, and the M.S. and Ph.D. degrees from UC Berkeley in 2005 and 2009, respectively. Since 2009, he has been with the Department of Electrical Engineering and Computer Science at the University of Michigan, Ann Arbor, where he is currently a full professor. His research primarily focuses on low-power and high-performance VLSI circuits and systems, with applications in computing, communications, and signal processing. Dr. Zhang was a recipient of the NSF CAREER Award, the Intel Early Career Faculty Award, the University of Michigan Neil Van Eenam Memorial Award, and the David J. Sakrison Memorial Prize from UC Berkeley. He serves as an IEEE Solid-State Circuits Society Distinguished Lecturer.

Title:
Task-oriented Communications for Edge AI
Date:
March 14th
5:30 PM (1 hour)
Abstract:

Discover the future of edge AI in our upcoming talk by Dr. Jun Zhang, an IEEE Fellow and Associate Professor at the Hong Kong University of Science and Technology. Delve into the shift from traditional data-oriented communications to task-oriented approaches, optimizing data transmission for specific inference tasks. Learn about the development of effective feature encoders and the introduction of EdgeGPT, an autonomous edge AI system. This presentation will highlight innovations in edge video analytics and mobile robotics, offering insights into achieving high accuracy and low latency in resource-constrained devices. Join us to explore cutting-edge strategies for enhancing edge computing solutions.

 

Abstract

Deep learning has achieved remarkable successes in many application domains, such as computer vision, image processing, and natural language processing. However, deploying powerful deep learning models on resource-constrained mobile devices (e.g., wearable or IoT devices) faces great challenges. Recently, edge AI techniques that rely on the emerging mobile edge computing platforms have been proposed, which forward intermediate features to be processed by a powerful edge server. To achieve high-accuracy and low-latency inference, effective feature encoders with low complexity and high compression capability will be needed. This calls for a paradigm shift in wireless communications, from “data-oriented communications”, which maximize data rates, to “task-oriented communications”, where the data transmission is an intermediate step to be optimized for the downstream inference task. This talk will introduce recent progresses on task-oriented communication for edge inference. An effective design principle based on information bottleneck will be firstly introduced, which will then be extended to multi-device cooperative perception based on a distributed information bottleneck framework. Use cases on edge video analytics and edge-assisted localization for mobile robots will be presented, followed by introduction of EdgeGPT, an autonomous edge AI system empowered by large language models.

Bio:

Jun Zhang received his Ph.D. degree in Electrical and Computer Engineering from the University of Texas at Austin. He is an IEEE Fellow and an IEEE ComSoc Distinguished Lecturer. He is an Associate Professor in the Department of Electronic and Computer Engineering at the Hong Kong University of Science and Technology. His research interests include wireless communications and networking, mobile edge computing and edge AI, and cooperative AI. Dr. Zhang co-authored the book Fundamentals of LTE (Prentice-Hall, 2010). He is a co-recipient of several best paper awards, including the 2021 Best Survey Paper Award of IEEE Communications Society, the 2019 IEEE Communications Society & Information Theory Society Joint Paper Award, and the 2016 Marconi Prize Paper Award in Wireless Communications. He also received the 2016 IEEE ComSoc Asia-Pacific Best Young Researcher Award. He is an Editor of IEEE Transactions on Communications and IEEE Transactions on Machine Learning in Communications and Networking, and was an editor of IEEE Transactions on Wireless Communications (2015-2020).

Title:
Journey through the Cosmos: A Woman Engineer's Exploration in Astrophysics
Date:
March 25th
6:30 PM (1.5 hours)
Abstract:

We are thrilled to announce that we will explore the vast realm of astrophysics with our esteemed invited speaker, Dr. Akhter. Dr. Akhter serves as a lecturer in Astrophysics and Physics at the University of Wollongong, bringing a wealth of expertise and knowledge to our event

Title:
SusTech Talk - Groundwater as a Rescue for Sustaining Agriculture with Farmer’s Decision
Date:
March 26th
6:00 PM (1 hour)
Abstract:

SusTech is hosting talks on Sustainability topics leading up to the 2024 conference in April.

“Groundwater as a Rescue for Sustaining Agriculture with Farmer’s Decision”

with Shakeel Ahmed, Visiting Professor, Islamic University of Science and Technology, J&K, India; Former Chief Scientist, CSIR - National Geophysical Research Institute and former Team-Leader, Indo-French Centre for Groundwater Research, Hyderabad, India

Date/Time:

Tuesday, 26-March-2024, 9-10 pm US Eastern, 6-7 pm US Pacific

 

6 meetings. Generated Tuesday, February 27 2024, at 1:16:42 PM. All times America/Los_Angeles