DesignCon is the premier high-speed communications and system design conference and exposition, now in its 30th year, with a (https://dcon25.mapyourshow.com/8_0/explore/session-gallery.cfm) with more than 180 educational sessions covering all aspects of chip, board, and systems design; an expo with access to over (https://dcon25.mapyourshow.com/8_0/explore/exhibitor-gallery.cfm?featured=false); open-to-all daily (https://www.designcon.com/en/education/keynotes.html) by engineering visionaries; 78 (https://dcon25.mapyourshow.com/8_0/explore/session-gallery.cfm?sessioncategory9=68); (https://www.designcon.com/en/expo/networking.html) including a Welcome Reception, daily booth bar crawls, and multiple (https://www.designcon.com/en/expo/30th-anniversary.html); and more. IEEE-CNSV officers and members, and local IEEE officers, will be in Booth #515 on the Exhibition Floor. As a friend of CNSV, you can (https://utm.io/uhX2z) with the promo code ENGAGE25 for 15% off all conference passes or a FREE expo pass. Onsite expo admission is $279. Santa Clara Convention Center , 5001 Great America Pkwy, Santa Clara, California, United States, 95054

Fog learning is an emerging paradigm for optimizing the orchestration of artificial intelligence services over contemporary network systems. Different from existing distributed techniques such as federated learning, fog learning emphasizes intrinsically in its design the unique node, network, and data properties encountered in today's fog networks that span computing elements from the edge to the cloud. An important thread of research in fog learning has been on understanding the role that local topologies formed on an ad-hoc basis among proximal groups of heterogeneous computing elements can play in elevating the achievable tradeoff between intelligence quality and resource efficiency. In this talk, I will discuss recent results on the analysis of fog learning processes which give insights into the impact that these topologies, along with other properties such as model characteristics and fog decision parameters, have on global training performance. Additionally, I will discuss the development of adaptive control methodologies that leverage such relationships for jointly optimizing relevant fog learning metrics. Speaker(s): Dr. Christopher Brinton Agenda: Networking: 4:00 PM to 4:30 PM (Refreshments will be provided) Presentation: 4:30 PM to 5:15 PM Q&A: 5:15 PM to 5:45 PM Networking: 5:45 PM to 6:00 PM Room: 206, Bldg: Daly Science Center, Santa Clara University, Santa Clara, California, United States, 95050

Our inaugural talk of the 2025 Invited Seminar Series comprises of two back to back talks covering a few interesting topics revolving around cloud computing including user access control, authentication and authorization, deploying machine learning models and accelerating ML workflow on the cloud platforms. Co-sponsored by: Media Partner: Open Research Institute (ORI) Speaker(s): Saidaiah Yachuri, Kunal Sekhri Agenda: - Invited talk from (https://www.linkedin.com/in/saidaiah-yechuri-1257bb14/), SDE at Amazon Web Services(25 mins) - Invited talk from (https://www.linkedin.com/in/kunalsekhri/), Senior SW Engg. at Google (25 mins) - Q/A Session (10 mins) Virtual: https://events.vtools.ieee.org/m/460746