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:20260310T211743Z UID:E32A19C2-1144-4646-A701-34D1E6FD9D56 DTSTART;TZID=America/New_York:20260424T140000 DTEND;TZID=America/New_York:20260424T150000 DESCRIPTION:Zoom Link: https://ulaval.zoom.us/j/65778451409?pwd=B1j19PbbWPh yXWjxkTf9PjOfIekUCY.1\n\n[Ahmed Alkhateeb]\n\nTalk Abstract:\n\nDigital tw ins of the wireless environments offer new capabilities to the communicati on network design and operation. They could be utilized offline to build s ite-specific datasets for pre-training and evaluation machine learning mod els\, or online to provide real-time or near real-time priors that aid the various communication system decisions on precoding\, channel estimation\ , spectrum sharing\, resource allocation\, among many interesting applicat ions. In this talk\, I will present key aspects and considerations for mod eling\, building\, calibrating\, and utilizing these digital twins to maxi mize their gains while balancing constraints on cost\, latency\, and compu tational overhead. I will also introduce DeepVerse 6G\, the world’s firs t large-scale digital-twin research platform\, which provides high-fidelit y multi-modal sensing and communication “true” digital twin datasets t o accelerate research and development across a wide range of applications. \n\nSpeaker Biography:\n\nAhmed Alkhateeb received his B.S. and M.S. degre es in Electrical Engineering from Cairo University\, Egypt\, in 2008 and 2 012\, and his Ph.D. degree in Electrical and Computer Engineering from The University of Texas at Austin\, USA\, in 2016. After the Ph.D.\, he spent some time as a Wireless Communications Researcher at the Connectivity Lab \, Facebook\, before joining Arizona State University (ASU) in the Spring of 2018\, where he is currently an Associate Professor in the School of El ectrical\, Computer\, and Energy Engineering. His research interests are i n the broad areas of wireless communications\, signal processing\, machine learning\, and applied math. Dr. Alkhateeb is the recipient of the 2012 M CD Fellowship from The University of Texas at Austin\, the 2016 IEEE Signa l Processing Society Young Author Best Paper Award for his work on hybrid precoding and channel estimation in millimeter-wave communication systems\ , and the NSF CAREER Award 2021 to support his research on leveraging mach ine learning for large-scale MIMO systems.\n\nMeeting Link: https://ulaval .zoom.us/j/65778451409?pwd=B1j19PbbWPhyXWjxkTf9PjOfIekUCY.1\, Québec City \, Quebec\, Canada\, G1X 4C5 LOCATION:Meeting Link: https://ulaval.zoom.us/j/65778451409?pwd=B1j19PbbWPh yXWjxkTf9PjOfIekUCY.1\, Québec City\, Quebec\, Canada\, G1X 4C5 ORGANIZER:md-zoheb.hassan@gel.ulaval.ca SEQUENCE:42 SUMMARY:IEEE Québec Seminar: Wireless Digital Twins: Key Considerations fo r Modeling\, Building\, Tuning\, and Utilization URL;VALUE=URI:https://events.vtools.ieee.org/m/546262 X-ALT-DESC:Description: <br /><p>Zoom Link: <a href="https://ulaval.zoom.us /j/65778451409?pwd=B1j19PbbWPhyXWjxkTf9PjOfIekUCY.1">https://ulaval.zoom.u s/j/65778451409?pwd=B1j19PbbWPhyXWjxkTf9PjOfIekUCY.1</a>&nbsp\;</p>\n<p><i mg style="display: block\; margin-left: auto\; margin-right: auto\;" src=" https://webapp4.asu.edu/photo-ws/directory_photo/alkhateb?size=medium&amp\ ;break=1773174071&amp\;blankImage2=1" alt="Ahmed Alkhateeb" width="200cm" height="200cm"></p>\n<p style="text-align: left\;"><strong>Talk Abstract:< /strong></p>\n<p><span data-olk-copy-source="MessageBody">Digital twins of the wireless environments offer new capabilities to the communication net work design and operation. They could be utilized offline to build site-sp ecific datasets for pre-training and evaluation machine learning models\, or online to provide real-time or near real-time priors that aid the vario us communication system decisions on precoding\, channel estimation\, spec trum sharing\, resource allocation\, among many interesting applications. In this talk\, I will present key aspects and considerations for modeling\ , building\, calibrating\, and utilizing these digital twins to maximize t heir gains while balancing constraints on cost\, latency\, and computation al overhead. I will also introduce DeepVerse 6G\, the world&rsquo\;s first large-scale digital-twin research platform\, which provides high-fidelity multi-modal sensing and communication &ldquo\;true&rdquo\; digital twin d atasets to accelerate research and development across a wide range of appl ications.</span></p>\n<p style="text-align: justify\;"><strong>Speaker Bio graphy:</strong></p>\n<p style="text-align: justify\;">Ahmed Alkhateeb rec eived his B.S. and M.S. degrees in Electrical Engineering from Cairo Unive rsity\, Egypt\, in 2008 and 2012\, and his Ph.D. degree in Electrical and Computer Engineering from The University of Texas at Austin\, USA\, in 201 6. After the Ph.D.\, he spent some time as a Wireless Communications Resea rcher at the Connectivity Lab\, Facebook\, before joining Arizona State Un iversity (ASU) in the Spring of 2018\, where he is currently an Associate Professor in the School of Electrical\, Computer\, and Energy Engineering. His research interests are in the broad areas of wireless communications\ , signal processing\, machine learning\, and applied math. Dr. Alkhateeb i s the recipient of the 2012 MCD Fellowship from The University of Texas at Austin\, the 2016 IEEE Signal Processing Society Young Author Best Paper Award for his work on hybrid precoding and channel estimation in millimete r-wave communication systems\, and the NSF CAREER Award 2021 to support hi s research on leveraging machine learning for large-scale MIMO systems.</p >\n<p>&nbsp\;</p> END:VEVENT END:VCALENDAR