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UID:3AB5F67A-6435-451F-AB70-9B19C7C9A2BA
DTSTART;TZID=US/Eastern:20211122T110000
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DESCRIPTION:IEEE Communications Society\, Mohawk Valley chapter cordially i
 nvites you to a (virtual) technical seminar &quot;Machine Learning Aided 6G: Le
 veraging Sensory Data for Highly-Mobile and Reliable Communication Systems
 &quot; by Dr. Ahmed Alkhateeb from Arizona State University. Dr. Alkhateeb’s 
 latest research and data sets can be found here: https://viwi-dataset.net/
  and https://www.deepmimo.net/\n\nAbstract: Advanced communications and si
 gnal processing for millimeter-wave (mmWave) and terahertz (THz) frequenci
 es will be key enabling technologies for next generation wireless communic
 ations systems such as 6G and beyond. The communication over these frequen
 cy bands\, however\, is subject to critical challenges\, such as the large
  training overhead associated with adjusting the narrow beams and the high
  sensitivity to blockages. These challenges make it difficult for mmWave/T
 Hz MIMO systems to support applications like virtual/augmented reality and
  vehicular communications that have high mobility and strict reliability/l
 atency constraints. In this talk\, I will present DeepSense 6G\, a large-s
 cale real-world dataset that enables multi-modal sensing and communication
  deep learning research. I will go over the dataset structure and the avai
 lable scenarios. Then\, I will present some of the applications and machin
 e learning tasks enabled by the dataset such as position\, radar\, LiDAR\,
  and camera aided beam prediction\, and sensing-aided proactive blockage p
 rediction. Finally\, I will provide a brief overview of other relevant res
 earch directions\, including the interplay between communications\, imagin
 g\, and localization at above 100GHz\, and the integration of large intell
 igent surfaces in future wireless systems.\n\nBio: Ahmed Alkhateeb receive
 d his B.S. degree (distinction with honor) and M.S. degree in Electrical E
 ngineering from Cairo University\, Egypt\, in 2008 and 2012\, and his Ph.D
 . degree in Electrical Engineering from The University of Texas at Austin\
 , USA\, in August 2016. In Sept. 2016- Dec. 2017\, he was a Wireless Commu
 nications Researcher at the Connectivity Lab\, Facebook\, in Menlo Park\, 
 CA. He joined Arizona State University (ASU) in Spring 2018\, where he is 
 currently an Assistant Professor in the School of Electrical\, Computer\, 
 and Energy Engineering. He has held R&amp;D internships at FutureWei Technolog
 ies (Huawei) in Chicago\, IL\, and Samsung Research America (SRA) in Dalla
 s\, TX. His research interests are in the broad areas of wireless communic
 ations\, communication theory\, signal processing\, machine learning\, and
  applied math. Dr. Alkhateeb is the recipient of the 2012 MCD Fellowship f
 rom The University of Texas at Austin\, the 2016 IEEE Signal Processing So
 ciety Young Author Best Paper Award for his work on hybrid precoding and c
 hannel estimation in millimeter-wave communication systems\, and the NSF C
 AREER Award 2021 to support his research on leveraging machine learning fo
 r large-scale MIMO systems.\n\n[Join WebEx meeting](https://ieeemeetings.w
 ebex.com/ieeemeetings/j.php?MTID=mc0d54043ec6908b62e53330301054fe4)\n\nhtt
 ps://ieeemeetings.webex.com/ieeemeetings/j.php?MTID=mc0d54043ec6908b62e533
 30301054fe4\n\nMeeting number:	2534 325 2836\nMeeting password:	aYpggp4Nw3
 3\n\nJoin from a video system or application\n\nDial 25343252836@ieeemeeti
 ngs.webex.com\nYou can also dial 173.243.2.68 and enter your meeting numbe
 r.\nTo dial from an IEEE Video Conference System: *1 2534 325 2836\n\nTap 
 to join from a mobile device (attendees only)\n\n[+1-415-655-0002\,\,25343
 252836##](tel:%2B1-415-655-0002\,\,*01*25343252836%23%23*01*) United State
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 0c2bdff0c6e1ac5e8) to your calendar. (Cannot add from mobile devices.)\n\n
 Speaker(s): Dr. Ahmed Alkhateeb\, \n\nAgenda: \nTechnical seminar followed
  by Q&amp;A session.\n\nRome\, New York\, United States\, Virtual: https://eve
 nts.vtools.ieee.org/m/289704
LOCATION:Rome\, New York\, United States\, Virtual: https://events.vtools.i
 eee.org/m/289704
ORGANIZER:ngwethawdar@ieee.org
SEQUENCE:1
SUMMARY:Technical Seminar: Machine Learning Aided 6G: Leveraging Sensory Da
 ta for Highly-Mobile and Reliable Communication Systems
URL;VALUE=URI:https://events.vtools.ieee.org/m/289704
X-ALT-DESC:Description: &lt;br /&gt;&lt;p&gt;IEEE Communications Society\, Mohawk Valle
 y chapter cordially invites you to a (virtual) technical seminar &quot;Machine 
 Learning Aided 6G: Leveraging Sensory Data for Highly-Mobile and Reliable 
 Communication Systems&quot; by&amp;nbsp\; Dr. Ahmed Alkhateeb from Arizona State Un
 iversity. Dr. Alkhateeb&amp;rsquo\;s latest research and data sets can be foun
 d here:&amp;nbsp\;&lt;a href=&quot;https://viwi-dataset.net/&quot; target=&quot;_blank&quot; rel=&quot;noo
 pener&quot; data-saferedirecturl=&quot;https://www.google.com/url?q=https://viwi-dat
 aset.net/&amp;amp\;source=gmail&amp;amp\;ust=1636757012229000&amp;amp\;usg=AOvVaw28NdY
 LtwCSD_Bo54CydBsj&quot;&gt;https://viwi-dataset.&lt;wbr /&gt;net/&lt;/a&gt;&amp;nbsp\;and&amp;nbsp\;&lt;a
  href=&quot;https://www.deepmimo.net/&quot; target=&quot;_blank&quot; rel=&quot;noopener&quot; data-safe
 redirecturl=&quot;https://www.google.com/url?q=https://www.deepmimo.net/&amp;amp\;s
 ource=gmail&amp;amp\;ust=1636757012229000&amp;amp\;usg=AOvVaw2-JZ6F5D6Rp5oLq-l1cf4
 h&quot;&gt;https://www.deepmimo.net/&lt;/a&gt;&amp;nbsp\;&lt;/p&gt;\n&lt;p style=&quot;font-weight: 400\;&quot;
 &gt;&lt;strong&gt;Abstract:&lt;/strong&gt;&amp;nbsp\;Advanced communications and signal proce
 ssing for millimeter-wave (mmWave) and terahertz (THz) frequencies will be
  key enabling technologies for next generation wireless communications sys
 tems such as 6G and beyond. The communication over these frequency bands\,
  however\, is subject to critical challenges\, such as the large training 
 overhead associated with adjusting the narrow beams and the high sensitivi
 ty to blockages. These challenges make it difficult for mmWave/THz MIMO sy
 stems to support applications like virtual/augmented reality and vehicular
  communications that have high mobility and strict reliability/latency con
 straints. In this talk\, I will present DeepSense 6G\, a large-scale real-
 world dataset that enables multi-modal sensing and communication deep lear
 ning research. I will go over the dataset structure and the available scen
 arios. Then\, I will present some of the applications and machine learning
  tasks enabled by the dataset such as position\, radar\, LiDAR\, and camer
 a aided beam prediction\, and sensing-aided proactive blockage prediction.
  Finally\, I will provide a brief overview of other relevant research dire
 ctions\, including the interplay between communications\, imaging\, and lo
 calization at above 100GHz\, and the integration of large intelligent surf
 aces in future wireless systems.&lt;br /&gt;&lt;br /&gt;&lt;strong&gt;Bio:&lt;/strong&gt;&amp;nbsp\;Ah
 med Alkhateeb received his B.S. degree (distinction with honor) and M.S. d
 egree in Electrical Engineering from Cairo University\, Egypt\, in 2008 an
 d 2012\, and his Ph.D. degree in Electrical Engineering from The Universit
 y of Texas at Austin\, USA\, in August 2016. In Sept. 2016- Dec. 2017\, he
  was a Wireless Communications Researcher at the Connectivity Lab\, Facebo
 ok\, in Menlo Park\, CA. He joined Arizona State University (ASU) in Sprin
 g 2018\, where he is currently an Assistant Professor in the School of Ele
 ctrical\, Computer\, and Energy Engineering. He has held R&amp;amp\;D internsh
 ips at FutureWei Technologies (Huawei) in Chicago\, IL\, and Samsung Resea
 rch America (SRA) in Dallas\, TX. His research interests are in the broad 
 areas of wireless communications\, communication theory\, signal processin
 g\, machine learning\, and applied math. Dr. Alkhateeb is 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 millimeter-wave communicati
 on systems\, and the NSF CAREER Award 2021 to support his research on leve
 raging machine learning for large-scale MIMO systems.&lt;/p&gt;\n&lt;p&gt;&amp;nbsp\;&lt;/p&gt;\
 n&lt;table style=&quot;font-weight: 400\;&quot;&gt;\n&lt;tbody&gt;\n&lt;tr&gt;\n&lt;td&gt;&amp;nbsp\;&lt;/td&gt;\n&lt;/tr
 &gt;\n&lt;/tbody&gt;\n&lt;/table&gt;\n&lt;table style=&quot;font-weight: 400\;&quot;&gt;\n&lt;tbody&gt;\n&lt;tr&gt;\n
 &lt;td&gt;&lt;a href=&quot;https://ieeemeetings.webex.com/ieeemeetings/j.php?MTID=mc0d54
 043ec6908b62e53330301054fe4&quot; data-saferedirecturl=&quot;https://www.google.com/
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 =&quot;https://ieeemeetings.webex.com/ieeemeetings/j.php?MTID=mc0d54043ec6908b6
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 ://ieeemeetings.webex.com/ieeemeetings/j.php?MTID%3Dmc0d54043ec6908b62e533
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 d&gt;\n&lt;/tr&gt;\n&lt;/tbody&gt;\n&lt;/table&gt;\n&lt;p&gt;&amp;nbsp\;&lt;/p&gt;&lt;br /&gt;&lt;br /&gt;Agenda: &lt;br /&gt;&lt;p&gt;
 Technical seminar followed by Q&amp;amp\;A session.&lt;/p&gt;
END:VEVENT
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