BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VEVENT DTSTAMP:20260824T212223Z UID:DD434376-8BE9-4CA8-8ACC-F460FECAC4FA DTSTART;TZID=Etc/UTC:20260917T120000 DTEND;TZID=Etc/UTC:20260917T130000 DESCRIPTION:[Enabling Trustworthy Systems through Neuro-Symbolic AI with Ap plications in Communications and Networking]\n\nSpecial Presentation by Ho ubing Herbert Song (U. of Maryland\, USA)\n\nHosted by the Future Networks Artificial Intelligence & Machine Learning (AIML) Working Group\n\nDate/T ime: Thursday\, 17 September 2026 @ 12:00 UTC (8 AM EDT)\n\nTopic:\n\nEnab ling Trustworthy Systems through Neuro-Symbolic AI with Applications in Co mmunications and Networking\n\nAbstract:\n\nAI is increasingly embedded in communications\, networking\, cybersecurity\, autonomous systems\, and th e Internet of Things\, making trustworthiness essential for consequential decisions. Yet\, data-driven AI remains challenged by explainability\, rob ustness\, security\, verifiability\, and alignment with human values. This talk presents neuro-symbolic AI as a foundation for trustworthy intellige nt systems\, combining neural learning and perception with symbolic knowle dge\, logical reasoning\, and explicit constraints. This integration offer s a pathway toward AI systems that can learn from data while reasoning abo ut context and consequences\, explaining decisions\, detecting contradicti ons\, resisting adversarial manipulation\, and operating within safety and security boundaries. The talk will highlight applications in communicatio ns and networking\, with particular emphasis on NeuroBA: Neuro-Symbolic Bi trate Adaptation for IRS-Aided Mobile Video Streaming\, demonstrating how neuro-symbolic learning and reasoning can enhance the intelligence\, adapt ability\, robustness\, and trustworthiness of AI-enabled communication sys tems. Ultimately\, the talk advances a vision of communications and networ king systems that are not merely intelligent and efficient\, but trustwort hy by design — systems that can learn\, reason\, adapt\, and make decisi ons worthy of human trust.\n\nSpeaker:\n\n[Kelvin Lopes Dias]\nDr. Houbing Herbert Song is a Tenured Full Professor and Director of the Security and Optimization for Networked Globe (SONG) Laboratory at the University of M aryland\, Baltimore County (UMBC). He received his Ph.D. in Electrical Eng ineering from the University of Virginia in 2012 and is an elected member of the European Academy of Engineering (EAE)\, an IEEE Fellow and ACM Dist inguished Member. His research focuses on neuro-symbolic AI\, trustworthy artificial intelligence\, anomaly detection\, Artificial Intelligence of T hings (AIoT)\, autonomous systems\, and cyber-physical systems. His work h as been widely supported by NSF\, NASA\, USDOT\, and FAA\, and has been fe atured in major media outlets including IEEE Spectrum and U.S. News & Worl d Report. Dr. Song serves as Co-Editor-in-Chief of IEEE Transactions on In dustrial Informatics\, Area Editor of IEEE Internet of Things Journal\, an d holds leadership roles in multiple IEEE and ACM initiatives\, including founding the ACM EIGTRUST and IEEE TRUST-IoT Working Group. He has also se rved as general chair and technical program chair for numerous flagship in ternational conferences. He is an ACM Distinguished Speaker\, IEEE Compute r Society Distinguished Visitor\, and IEEE Distinguished Lecturer across m ultiple societies. His honors include the IEEE Harry Rowe Mimno Award\, Re search.com Rising Star of Science Award\, multiple best paper awards\, and recognition as a Highly Cited Researcher.\n\nBrochure (PDF): [Webinar-AIM L-2026-09-17-Song-TrustNeuroSymbolicAI-Brochure.pdf](https://drive.google. com/file/d/16qeUQK82VhQIwuEVBdSwoLt6VHqSNs8M/view)\n\nCo-sponsored by: Fut ure Networks Artificial Intelligence & Machine Learning (AIML) Working Gro up\n\nVirtual: https://events.vtools.ieee.org/m/573946 LOCATION:Virtual: https://events.vtools.ieee.org/m/573946 ORGANIZER:baw@ieee.org SEQUENCE:41 SUMMARY:Enabling Trustworthy Systems through Neuro-Symbolic AI with Applica tions in Communications and Networking URL;VALUE=URI:https://events.vtools.ieee.org/m/573946 X-ALT-DESC:Description: <br /><p class="MsoNormal" style="margin-top: .25in \;"><img src="https://events.vtools.ieee.org/vtools_ui/media/display/149a5 da9-1e03-40d6-acb9-166dc6b59088" alt="Enabling Trustworthy Systems through Neuro-Symbolic AI with Applications in Communications and Networking" wid th="750" height="197"></p>\n<p class="MsoNormal" style="margin-top: 12.0pt \;">Special Presentation by<strong> Houbing Herbert Song (U. of Maryland\, USA)</strong></p>\n<p class="MsoNormal" style="margin-top: 12.0pt\;">Host ed by the Future Networks<strong> Artificial Intelligence &amp\; Machine L earning (AIML) Working Group</strong></p>\n<p class="MsoNormal" style="mar gin-top: 12.0pt\;"><strong><span style="font-size: 14.0pt\; font-family: C opperplate\; mso-fareast-font-family: PMingLiU\; mso-fareast-theme-font: m inor-fareast\; mso-bidi-font-family: Arial\; mso-bidi-theme-font: minor-bi di\; mso-ansi-language: EN-US\; mso-fareast-language: ZH-TW\; mso-bidi-lan guage: AR-SA\;">Date/Time</span></strong><span style="font-size: 12.0pt\; font-family: 'Calibri'\,sans-serif\; mso-ascii-theme-font: minor-latin\; m so-fareast-font-family: PMingLiU\; mso-fareast-theme-font: minor-fareast\; mso-hansi-theme-font: minor-latin\; mso-bidi-font-family: Arial\; mso-bid i-theme-font: minor-bidi\; mso-ansi-language: EN-US\; mso-fareast-language : ZH-TW\; mso-bidi-language: AR-SA\;">: <strong>Thursday\, 17 September 20 26</strong><strong> @ 12:00 UTC (8 AM EDT)</strong></span></p>\n<p class=" MsoNormal" style="margin-top: .25in\;"><strong><u><span style="font-size: 16.0pt\; font-family: Copperplate\;">Topic</span></u></strong><strong><spa n style="font-size: 16.0pt\; font-family: Copperplate\;">:</span></strong> </p>\n<p class="MsoNormal"><strong><span style="font-size: 16pt\;">Enablin g Trustworthy Systems through Neuro-Symbolic AI with Applications in Commu nications and Networking&nbsp\;</span></strong></p>\n<p class="MsoNormal" style="margin-top: .25in\;"><strong><u><span style="font-size: 16.0pt\; fo nt-family: Copperplate\;">Abstract</span></u></strong><strong><span style= "font-size: 16.0pt\; font-family: Copperplate\;">:</span></strong></p>\n<p >AI is increasingly embedded in communications\, networking\, cybersecurit y\, autonomous systems\, and the Internet of Things\, making trustworthine ss essential for consequential decisions. Yet\, data-driven AI remains cha llenged by explainability\, robustness\, security\, verifiability\, and al ignment with human values. This talk presents neuro-symbolic AI as a found ation for trustworthy intelligent systems\, combining neural learning and perception with symbolic knowledge\, logical reasoning\, and explicit cons traints. This integration offers a pathway toward AI systems that can lear n from data while reasoning about context and consequences\, explaining de cisions\, detecting contradictions\, resisting adversarial manipulation\, and operating within safety and security boundaries. The talk will highlig ht applications in communications and networking\, with particular emphasi s on <em>NeuroBA: Neuro-Symbolic Bitrate Adaptation for IRS-Aided Mobile V ideo Streaming</em>\, demonstrating how neuro-symbolic learning and reason ing can enhance the intelligence\, adaptability\, robustness\, and trustwo rthiness of AI-enabled communication systems. Ultimately\, the talk advanc es a vision of communications and networking systems that are not merely i ntelligent and efficient\, but trustworthy by design &mdash\; systems that can learn\, reason\, adapt\, and make decisions worthy of human trust.</p >\n<p><strong><span style="font-size: 16.0pt\; font-family: Copperplate\;" ><u>Speaker</u>:</span></strong></p>\n<table style="border-collapse: colla pse\; width: 100%\;" border="1"><colgroup><col style="width: 14.779271%\;" ><col style="width: 85.12476%\;"></colgroup>\n<tbody>\n<tr>\n<td><img src= "https://events.vtools.ieee.org/vtools_ui/media/display/aea438c3-0790-4256 -ba4e-41e59d8d58be" alt="Kelvin Lopes Dias" width="213" height="230"></td> \n<td>\n<p class="MsoNormal" style="margin-top: 6.0pt\;">Dr.&nbsp\;<strong >Houbing Herbert Song</strong> is a Tenured Full Professor and Director of the Security and Optimization for Networked Globe (SONG) Laboratory at th e University of Maryland\, Baltimore County (UMBC). He received his Ph.D. in Electrical Engineering from the University of Virginia in 2012 and is a n elected member of the European Academy of Engineering (EAE)\, an IEEE Fe llow and ACM Distinguished Member.&nbsp\;His research focuses on neuro-sym bolic AI\, trustworthy artificial intelligence\, anomaly detection\, Artif icial Intelligence of Things (AIoT)\, autonomous systems\, and cyber-physi cal systems. His work has been widely supported by NSF\, NASA\, USDOT\, an d FAA\, and has been featured in major media outlets including IEEE Spectr um and U.S. News &amp\; World Report.&nbsp\;Dr. Song serves as Co-Editor-i n-Chief of IEEE Transactions on Industrial Informatics\, Area Editor of IE EE Internet of Things Journal\, and holds leadership roles in multiple IEE E and ACM initiatives\, including founding the ACM EIGTRUST and IEEE TRUST -IoT Working Group. He has also served as general chair and technical prog ram chair for numerous flagship international conferences.&nbsp\;He is an ACM Distinguished Speaker\, IEEE Computer Society Distinguished Visitor\, and IEEE Distinguished Lecturer across multiple societies. His honors incl ude the IEEE Harry Rowe Mimno Award\, Research.com Rising Star of Science Award\, multiple best paper awards\, and recognition as a Highly Cited Res earcher. &nbsp\;</p>\n</td>\n</tr>\n</tbody>\n</table>\n<p><strong>Brochur e (PDF)</strong>: <a title="Future Networks AI/ML: Enabling Trustworthy Sy stems through Neuro-Symbolic AI with Applications in Communications and Ne tworking" href="https://drive.google.com/file/d/16qeUQK82VhQIwuEVBdSwoLt6V HqSNs8M/view" target="_blank" rel="noopener">Webinar-AIML-2026-09-17-Song- TrustNeuroSymbolicAI-Brochure.pdf</a></p> END:VEVENT END:VCALENDAR