BEGIN:VCALENDAR
VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
DTSTART:20220313T030000
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3
TZNAME:EDT
END:DAYLIGHT
BEGIN:STANDARD
DTSTART:20221106T010000
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11
TZNAME:EST
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20220318T210101Z
UID:501E33CB-6422-4A8D-B2E1-CD4BCAC15877
DTSTART;TZID=America/New_York:20220315T190000
DTEND;TZID=America/New_York:20220315T203000
DESCRIPTION:Internet-of-Things (IoT) systems play an integral role in our d
 aily lives\, and we are currently witnessing an explosion of the IoT ecosy
 stem\, which includes not only smartphones but also smart\, ubiquitous obj
 ects embedded with communication\, computation\, and sensing capabilities.
  Emerging IoT systems\, such as autonomous vehicles\, immersive virtual an
 d augmented reality\, tactile internet\, holoportation\, and smart\, conne
 cted buildings\, promise to automate human lives at unprecedented levels t
 his decade. However\, such systems rely on two critical foundations: (1) N
 ext-generation wireless network architectures that can serve billions of d
 evices\; and (2) Ubiquitous sensing techniques that enable the objects to 
 be &quot;truly smart&quot; by understanding and interpreting the ambient conditions 
 and micro-activities with high precision.\n\nMy research team has been bui
 lding these two foundations. We design\, develop\, and deploy experimental
  data-driven computational and deep learning models to extract intelligenc
 e from wireless signals\, which\, in turn\, enable ubiquitous sensing moda
 lities and high-resilience and high-performance networks. In this talk\, I
  will go through some of the design and prototyping of our current works t
 hat use extremely high-frequency millimeter-wave wireless to enable wire-l
 ike connectivity and reliability\, and applications in healthcare and beyo
 nd-visions.\n\nSpeaker(s): Professor Sanjib Sur\, \n\nVirtual: https://eve
 nts.vtools.ieee.org/m/307159
LOCATION:Virtual: https://events.vtools.ieee.org/m/307159
ORGANIZER:aferraro@email.sc.edu
SEQUENCE:4
SUMMARY:Bringing Scalable Millimeter-Wave Networks and Applications to the 
 Masses
URL;VALUE=URI:https://events.vtools.ieee.org/m/307159
X-ALT-DESC:Description: &lt;br /&gt;&lt;p&gt;Internet-of-Things (IoT) systems play an i
 ntegral role in our daily lives\, and we are currently witnessing an explo
 sion of the IoT ecosystem\, which includes not only smartphones but also s
 mart\, ubiquitous objects embedded with communication\, computation\, and 
 sensing capabilities. Emerging IoT systems\, such as autonomous vehicles\,
  immersive virtual and augmented reality\, tactile internet\, holoportatio
 n\, and smart\, connected buildings\, promise to automate human lives at u
 nprecedented levels this decade. However\, such systems rely on two critic
 al foundations: (1) Next-generation wireless network architectures that ca
 n serve billions of devices\; and (2) Ubiquitous sensing techniques that e
 nable the objects to be &quot;truly smart&quot; by understanding and interpreting th
 e ambient conditions and micro-activities with high precision.&lt;/p&gt;\n&lt;p&gt;My 
 research team has been building these two foundations. We design\, develop
 \, and deploy experimental data-driven computational and deep learning mod
 els to extract intelligence from wireless signals\, which\, in turn\, enab
 le ubiquitous sensing modalities and high-resilience and high-performance 
 networks. In this talk\, I will go through some of the design and prototyp
 ing of our current works that use extremely high-frequency millimeter-wave
  wireless to enable wire-like connectivity and reliability\, and applicati
 ons in healthcare and beyond-visions.&lt;/p&gt;
END:VEVENT
END:VCALENDAR

