Generative Adversarial Networks (GANs) implement Machine Learning (ML) algorithms that can address competitive resource allocation problems together with detection and mitigation of anomalous behavior. In this talk, we discuss their use in next-generation (NextG) communications within the context of cognitive networks to address i) spectrum sharing, ii) detecting anomalies, and iii) mitigating security attacks. GANs have the following advantages. First, they can learn and synthesize field data, which can be costly, time consuming, and non-repeatable. Second, they enable pre-training classifiers by using semi-supervised data. Third, they facilitate increased resolution. Fourth, they enable recovering corrupted bits in the spectrum. The talk will provide basics of GANs, a comparative discussion on different kinds of GANs, performance measures for GANs in computer vision and image processing as well as wireless applications, several datasets for wireless applications, performance measures for general classifiers, a survey of the literature on GANs for i)–iii) above, some simulation results, and future research directions. In the spectrum sharing problem, connections to cognitive wireless networks are established. Simulation results show that a particular GAN implementation is better than a convolutional auto encoder for an outlier detection problem in spectrum sensing. Speaker(s): Ender Ayanoglu, Virtual: https://events.vtools.ieee.org/m/466461

Dear Seattle Section Life and Senior Members, Many thanks to Joe Decuir for hosting the first 2025 Life and Senior Members gathering at his beautiful lakeside home in Redmond. We warmly invite you to join us for an enjoyable time of networking, great conversation, and delicious food! Resurrection meeting time and place: - Monday June 9th, 2025, 7-8:30pm - In person: (https://www.google.com/maps/search/18814+SE+42?entry=gmail&source=g)nd St, Issaquah, WA 98027 - On Zoom: https://washington.zoom.us/j/2366026940?omn=93231791978, Meeting ID: 236 602 6940 The Seattle Section had a Life Member Activities Group before. Last year we had a petition approve to re-start it. Joe Decuir is the interim chair: jdecuir@ieee.org. Proposed mission: Life Members and Senior members have had a chance to work, contribute and accumulate engineering wisdom. We should collect that wisdom, and pay it forward to the Young Professionals and the student members. Resurrection meeting proposed agenda: - Discuss our mission - Discuss how we want to assemble and distribute our work - Identify volunteer leaders – and conduct elections later this year - Plan a Kickoff meeting: where and when? please RSVP so Joe know how much food to have. Also, if you have dietary restrictions, Please let Joe know. Joe Decuir, IEEE Fellow E: jdecuir@ieee.org or jdecuir@uw.edu M: 425-985-1562 Co-sponsored by: IEEE Seattle Life member affinity Group Agenda: Resurrection meeting proposed agenda: - Discuss our mission - Discuss how we want to assemble and distribute our work - Identify volunteer leaders – and conduct elections later this year - Plan a Kickoff meeting: where and when? 18814 SE 42nd St,, WA 98027, Issaquah, Washington, United States, 98027, Virtual: https://events.vtools.ieee.org/m/486591

Free Registration (with a Zoom account; you can get one for free if you don't already have it. This requirement is to avoid Zoom bombing. Please sign in using the email address tied to your Zoom account — not necessarily the one you used to register for the event.): https://sjsu.zoom.us/meeting/register/vo5r9OqaSFuqKsuFcww7Cg Synopsis: AR/VR devices promise a new era of immersive computing, where our everyday experience is augmented with helpful information (Augmented Reality), or where we are immersed in fully virtual worlds (Virtual Reality). These systems fuse the physical world and the virtual world through computing resources to provide these immersive experiences rendered on the user's headset. As a result, it allows new opportunities for attackers to compromise the security and privacy of users that are not well understood. Towards understanding the security and privacy challenges in these systems, this talk presents a number of recent attacks we developed on AR/VR systems. One threat model exploits the shared computing resources used by multiple applications on a headset to extract information through side channels; we show attacks that spy on user activity or compromise privacy. Another threat model exploits the shared state among multiple users in a multi-user application, allowing malicious users to inject compromised information or to recover information they are not allowed to access. Other threat models include those that interfere with applications and cause the virtual model to become out of sync with the physical world, causing user motion sickness or bypassing safety guardrails. I will conclude with a discussion of potential defenses and ways to build more secure AR/VR experiences. --------------------------------------------------------------- By registering for this event, you agree that IEEE and the organizers are not liable to you for any loss, damage, injury, or any incidental, indirect, special, consequential, or economic loss or damage (including loss of opportunity, exemplary or punitive damages). The event will be recorded and will be made available for public viewing. Co-sponsored by: Vishnu S. Pendyala, SJSU Speaker(s): Dr. Vishnu S. Pendyala, Prof. Nael Abu-Ghazaleh Virtual: https://events.vtools.ieee.org/m/485364

EXCOM Meeting for IEEE PES Seattle Officers Virtual: https://events.vtools.ieee.org/m/452312

EXCOM Meeting for IEEE PES Seattle Officers Virtual: https://events.vtools.ieee.org/m/452313

Free Registration (with a Zoom account; you can get one for free if you don't already have it. This requirement is to avoid Zoom bombing. Please sign in using the email address tied to your Zoom account — not necessarily the one you used to register for the event.): https://sjsu.zoom.us/webinar/register/WN_DIDfdbkgRFeEd3JbzURIUQ Synopsis: How are machine learning algorithms able to answer questions from any nook and corner of the World Wide Web? How are trending hashtags from the near infinite microblog posts, unique visitors and other distinct counts in the near infinite website traffic determined? How do blogging websites avoid recommending articles a user has previously read? In general, how can we answer complex queries about enormous data streams without storing them entirely, in real-time? The answer often lies in clever approximation algorithms and data "sketches" that capture essential properties using vastly reduced space. The relentless flow of data in modern systems indeed presents significant challenges. These data streams are often too large to store and too fast to process exhaustively with traditional methods. This talk introduces key sketching and approximation techniques that help generate real-time data insights by processing data streams. --------------------------------------------------------------- By registering for this event, you agree that IEEE and the organizers are not liable to you for any loss, damage, injury, or any incidental, indirect, special, consequential, or economic loss or damage (including loss of opportunity, exemplary or punitive damages). The event will be recorded and will be made available for public viewing. Speaker(s): Dr. Vishnu S. Pendyala Virtual: https://events.vtools.ieee.org/m/482936