BEGIN:VCALENDAR
VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
DTSTART:20230312T030000
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3
TZNAME:EDT
END:DAYLIGHT
BEGIN:STANDARD
DTSTART:20231105T010000
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11
TZNAME:EST
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20230906T014245Z
UID:BD900661-5DF2-4321-8E30-AA2015332FB9
DTSTART;TZID=America/New_York:20230905T180000
DTEND;TZID=America/New_York:20230905T190000
DESCRIPTION:Data science aims to solve grand global challenges such as: det
 ecting and preventing disease in human populations\; revealing community s
 tructure in large social networks\; protecting our elections from cyber-th
 reats\, and improving the resilience of the electric power grid. Unlike tr
 aditional applications in computational science and engineering\, solving 
 these social problems at scale often raises new challenges because of the 
 sparsity and lack of locality in the data\, the need for research on scala
 ble algorithms and architectures\, and development of frameworks for solvi
 ng these real-world problems on high performance computers\, and for impro
 ved models that capture the noise and bias inherent in the torrential data
  streams. In this talk\, Bader will discuss the opportunities and challeng
 es in massive data science for applications in social sciences\, physical 
 sciences\, and engineering.\n\nSpeaker(s): David Bader\, \n\nAgenda: \n6:0
 0 PM - Opening\, updates\, introductions\n6:10 PM - Talk start\n7:00 PM - 
 Formal end of talk\; Q&A\n7:10 PM - Vote of thanks\; End of meeting\n\nVir
 tual: https://events.vtools.ieee.org/m/368258
LOCATION:Virtual: https://events.vtools.ieee.org/m/368258
ORGANIZER:sharan.kalwani@ieee.org
SEQUENCE:22
SUMMARY:Solving Global Grand Challenges with High Performance Data Analytic
 s
URL;VALUE=URI:https://events.vtools.ieee.org/m/368258
X-ALT-DESC:Description: <br /><p>Data science aims to solve grand global ch
 allenges such as: detecting and preventing disease in human populations\; 
 revealing community structure in large social networks\; protecting our el
 ections from cyber-threats\, and improving the resilience of the electric 
 power grid. Unlike traditional applications in computational science and e
 ngineering\, solving these social problems at scale often raises new chall
 enges because of the sparsity and lack of locality in the data\, the need 
 for research on scalable algorithms and architectures\, and development of
  frameworks for solving these real-world problems on high performance comp
 uters\, and for improved models that capture the noise and bias inherent i
 n the torrential data streams. In this talk\, Bader will discuss the oppor
 tunities and challenges in massive data science for applications in social
  sciences\, physical sciences\, and engineering.</p><br /><br />Agenda: <b
 r /><p>6:00 PM - Opening\, updates\, introductions<br />6:10 PM - Talk sta
 rt<br />7:00 PM - Formal end of talk\; Q&amp\;A<br />7:10 PM - Vote of tha
 nks\; End of meeting</p>
END:VEVENT
END:VCALENDAR