BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/New_York BEGIN:DAYLIGHT DTSTART:20260308T030000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:EDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20261101T010000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:EST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20260402T165942Z UID:20866597-DEC2-4034-821E-E9321359F95B DTSTART;TZID=America/New_York:20260507T180000 DTEND;TZID=America/New_York:20260507T190000 DESCRIPTION:[LoreTokens: Cognition\, not just Compression]\n\nSpecial Prese ntation by Omar Hashash (Virginia Tech\, USA)\n\nHosted by the Future Netw orks Artificial Intelligence & Machine Learning (AI/ML) Working Group\n\nD ate/Time: Thursday\, 7 May 2026 @ 6 PM Eastern Time (3 PM Pacific Time)\n\ nTopic:\n\nDigital Twins and World Models: Bridging Next-Generation AI\, W ireless\, and Robotics Systems\n\nAbstract:\n\nWireless systems (e.g.\, 6G ) and artificial intelligence (AI) are evolving towards agentic frameworks that autonomously interact with the physical world. This requires a shift towards AI architectures that support reasoning\, planning\, and complex inference to deal with the dynamic nature of real-world environments. In t his talk\, we will explore how the intersection of digital twins (DTs) and world models (WMs) plays a role in enabling these new architectures. With their inherent connection to the physical world\, the integration of WMs into next-generation networks provides a unique opportunity to develop adv anced levels of wireless intelligence. In particular\, WMs offer a structu red approach for capturing the intuitive physical laws that underpin our u nderstanding of “how the world works.” This ability is a cornerstone f or dealing with the countless unforeseen scenarios that humans encounter i n the real world. Here\, DTs play a prominent role in mirroring the physic al counterparts of autonomous agents (e.g.\, robots\, autonomous vehicles\ , etc.) into these WMs over the network. Hence\, the convergence of DTs an d WMs promises to unleash new forms of embodied AI that can advance the pe rformance of both the network and its agents. Nevertheless\, to realize th is fusion\, wireless systems should acquire core abilities such as percept ion\, abstraction\, and analogy. To provide these missing cognitive abilit ies and close the loop\, we will present the first cognitive architecture tailored to a wireless network. Ultimately\, this cognitive architecture s erves as a foundation for transitioning towards next generation AI-native networks in the beyond 6G era. Furthermore\, we will elucidate the design of the cognitive modules embedded into this cognitive architecture. Finall y\, we will conclude with a set of illustrative examples that showcase new experiences emerging at the intersection of DTs\, WMs\, and wireless netw orks.\n\nSpeaker:\n\n[]\nOmar Hashash (Member\, IEEE) received his B.E. in Communications and Electronics Engineering from Beirut Arab University\, Lebanon in 2019 and his M.E. in Electrical and Computer Engineering from t he American University of Beirut\, Lebanon in 2021. He received his Ph.D. from the Bradley Department of Electrical and Computer Engineering at Virg inia Tech in 2025. His research interests include artificial intelligence (AI)\, world models\, digital twins\, and edge intelligence. His impactful research in these fields has led to releasing the first vision of artific ial general intelligence (AGI)-native wireless systems for beyond 6G. He a lso led the discovery of the first test-time scaling law for physical AI. In spring 2024\, he was a visiting researcher with the Sakaguchi Lab at th e Institute of Science Tokyo. In summer 2024\, Omar held an R&I – R&D in ternship position in the Wireless Research Department at InterDigital Comm unications\, Inc.\, USA. He has served as a technical program committee me mber in multiple flagship IEEE conferences and is a frequent reviewer at s everal IEEE journals..\n\nBrochure (PDF): [Webinar-AIML-2026-05-07-Hashash -DigitalTwinsWorldModel-Brochure.pdf](https://drive.google.com/file/d/1l-X gy_EADke4fs6ylB1XzMa7A4wrmPaG/view)\n\nCo-sponsored by: Future Networks Ar tificial Intelligence & Machine Learning (AIML) Working Group\n\nVirtual: https://events.vtools.ieee.org/m/552648 LOCATION:Virtual: https://events.vtools.ieee.org/m/552648 ORGANIZER:baw@ieee.org SEQUENCE:18 SUMMARY:Digital Twins and World Models: Bridging Next-Generation AI\, Wirel ess\, and Robotics Systems URL;VALUE=URI:https://events.vtools.ieee.org/m/552648 X-ALT-DESC:Description: <br /><p class="MsoNormal" style="margin-top: .25in \;"><img src="https://events.vtools.ieee.org/vtools_ui/media/display/dd11f 821-e257-4e25-b3ae-56ce5e603643" alt="LoreTokens: Cognition\, not just Com pression" width="750" height="197"></p>\n<p class="MsoNormal" style="margi n-top: 12.0pt\;">Special Presentation by<strong> Omar Hashash (Virginia Te ch\, USA)</strong></p>\n<p class="MsoNormal" style="margin-top: 12.0pt\;"> Hosted by the Future Networks<strong> Artificial Intelligence &amp\; Machi ne Learning (AI/ML) Working Group</strong></p>\n<p class="MsoNormal" style ="margin-top: 12.0pt\;"><strong><span style="font-size: 14.0pt\; font-fami ly: Copperplate\; mso-fareast-font-family: PMingLiU\; mso-fareast-theme-fo nt: minor-fareast\; mso-bidi-font-family: Arial\; mso-bidi-theme-font: min or-bidi\; mso-ansi-language: EN-US\; mso-fareast-language: ZH-TW\; mso-bid i-language: AR-SA\;">Date/Time</span></strong><span style="font-size: 12.0 pt\; font-family: 'Calibri'\,sans-serif\; mso-ascii-theme-font: minor-lati n\; mso-fareast-font-family: PMingLiU\; mso-fareast-theme-font: minor-fare ast\; mso-hansi-theme-font: minor-latin\; mso-bidi-font-family: Arial\; ms o-bidi-theme-font: minor-bidi\; mso-ansi-language: EN-US\; mso-fareast-lan guage: ZH-TW\; mso-bidi-language: AR-SA\;">: <strong>Thursday\, 7 May 2026 </strong><strong>&nbsp\;@ 6 PM Eastern Time (3 PM Pacific Time)</strong></ span></p>\n<p class="MsoNormal" style="margin-top: .25in\;"><strong><u><sp an style="font-size: 16.0pt\; font-family: Copperplate\;">Topic</span></u> </strong><strong><span style="font-size: 16.0pt\; font-family: Copperplate \;">:</span></strong></p>\n<p class="MsoNormal"><strong><span style="font- size: 16pt\;">Digital Twins and World Models: Bridging Next-Generation AI\ , Wireless\, and Robotics Systems</span></strong></p>\n<p class="MsoNormal " style="margin-top: .25in\;"><strong><u><span style="font-size: 16.0pt\; font-family: Copperplate\;">Abstract</span></u></strong><strong><span styl e="font-size: 16.0pt\; font-family: Copperplate\;">:</span></strong></p>\n <p>Wireless systems (e.g.\, 6G) and artificial intelligence (AI) are evolv ing towards agentic frameworks that autonomously interact with the physica l world. This requires a shift towards AI architectures that support reaso ning\, planning\, and complex inference to deal with the dynamic nature of real-world environments. In this talk\, we will explore how the intersect ion of digital twins (DTs) and world models (WMs) plays a role in enabling these new architectures. With their inherent connection to the physical w orld\, the integration of WMs into next-generation networks provides a uni que opportunity to develop advanced levels of wireless intelligence. In pa rticular\, WMs offer a structured approach for capturing the intuitive phy sical laws that underpin our understanding of &ldquo\;how the world works. &rdquo\; This ability is a cornerstone for dealing with the countless unfo reseen scenarios that humans encounter in the real world. Here\, DTs play a prominent role in mirroring the physical counterparts of autonomous agen ts (e.g.\, robots\, autonomous vehicles\, etc.) into these WMs over the ne twork. Hence\, the convergence of DTs and WMs promises to unleash new form s of embodied AI that can advance the performance of both the network and its agents. Nevertheless\, to realize this fusion\, wireless systems shoul d acquire core abilities such as perception\, abstraction\, and analogy. T o provide these missing cognitive abilities and close the loop\, we will p resent the first cognitive architecture tailored to a wireless network. Ul timately\, this cognitive architecture serves as a foundation for transiti oning towards next generation AI-native networks in the beyond 6G era. Fur thermore\, we will elucidate the design of the cognitive modules embedded into this cognitive architecture. Finally\, we will conclude with a set of illustrative examples that showcase new experiences emerging at the inter section of DTs\, WMs\, and wireless networks.&nbsp\;</p>\n<p><strong><span style="font-size: 16.0pt\; font-family: Copperplate\;"><u>Speaker</u>:</s pan></strong></p>\n<table style="border-collapse: collapse\; width: 100%\; " border="1"><colgroup><col style="width: 17.466411%\;"><col style="width: 82.43762%\;"></colgroup>\n<tbody>\n<tr>\n<td><img src="https://events.vto ols.ieee.org/vtools_ui/media/display/febb8c0e-bba2-4f61-a2ff-c79ff04e5afc" alt="" width="172" height="200"></td>\n<td>\n<p><strong>Omar Hashash</str ong> (Member\, IEEE) received his B.E. in Communications and Electronics E ngineering from Beirut Arab University\, Lebanon in 2019 and his M.E. in E lectrical and Computer Engineering from the American University of Beirut\ , Lebanon in 2021. He received his Ph.D. from the Bradley Department of El ectrical and Computer Engineering at Virginia Tech in 2025. His research i nterests include artificial intelligence (AI)\, world models\, digital twi ns\, and edge intelligence. His impactful research in these fields has led to releasing the first vision of artificial general intelligence (AGI)-na tive wireless systems for beyond 6G. He also led the discovery of the firs t test-time scaling law for physical AI. In spring 2024\, he was a visitin g researcher with the Sakaguchi Lab at the Institute of Science Tokyo. In summer 2024\, Omar held an R&amp\;I &ndash\; R&amp\;D internship position in the Wireless Research Department at InterDigital Communications\, Inc.\ , USA. He has served as a technical program committee member in multiple f lagship IEEE conferences and is a frequent reviewer at several IEEE journa ls..</p>\n</td>\n</tr>\n</tbody>\n</table>\n<p><strong>Brochure (PDF)</str ong>: <a href="https://drive.google.com/file/d/1l-Xgy_EADke4fs6ylB1XzMa7A4 wrmPaG/view" target="_blank" rel="noopener">Webinar-AIML-2026-05-07-Hashas h-DigitalTwinsWorldModel-Brochure.pdf</a></p> END:VEVENT END:VCALENDAR