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UID:www.tcs.tifr.res.in/event/251
DTSTAMP:20230914T125916Z
SUMMARY:Large-scale Situation Awareness with Camera Networks and Multimodal
  Sensing
DESCRIPTION:Speaker: Kishore Ramachandran (Georgia Institute of Technology\
 ,\nCollege of Computing\,\nKlaus Advanced Computing Building\,\n266 Ferst 
 Dr.\, Atlanta\, GA 30332\nUnited States of America)\n\nAbstract: \nSensors
  of various modalities and capabilities\, especially cameras\, have become
  ubiquitous in our environment. Their intended use is wide ranging and enc
 ompasses surveillance\, transportation\, entertainment\, education\, healt
 hcare\, emergency response\, disaster recovery\, and the like. Technologic
 al advances and the low cost of such sensors enable deployment of large-sc
 ale camera networks in large metropolis such as London and New York. Multi
 media algorithms for analyzing and drawing inferences from video and audio
  have also matured tremendously in recent times. Despite all these advance
 s\, large-scale reliable systems for media-rich sensor-based applications\
 , often classified as situation awareness applications\, are yet to become
  commonplace. Why is that? There are several forces at work here. First of
  all\, the system abstractions are just not at the right level for quickly
  prototyping such applications in the large. Second\, while Moore’s law 
 has held true for predicting the growth of processing power\, the volume o
 f data that applications are called upon to handle is growing similarly\, 
 if not faster. Enormous amount of sensing data is continually generated fo
 r real-time analysis in such applications. Further\, due to the very natur
 e of the application domain\, there are dynamic and demanding resource req
 uirements for such analyses.\n\nThe lack of right set of abstractions for 
 programming such applications coupled with their data intensive nature hav
 e hitherto made realizing reliable large-scale situation awareness applica
 tions difficult. Incidentally\, situation awareness is a very popular but 
 ill-defined research area that has attracted researchers from many differe
 nt fields. In this talk\, I will adopt a systems perspective and consider 
 the components that are essential in realizing a fully functional situatio
 n awareness system.\n\nBio: Kishore Ramachandran received his Ph. D. in Co
 mputer Science from the University of Wisconsin\, Madison in 1986\, and ha
 s been on the faculty of Georgia Tech since then. Currently\, he is the Di
 rector of Samsung Tech Advanced Research (STAR) center\, Director of Korea
  Programs\, and Professor in the College of Computing at the Georgia Insti
 tute of Technology. For two years (July 2003 to August 2005) he served as 
 the Chair of the Core Computing Division within the College of Computing. 
 His fields of interest include parallel and distributed systems\, computer
  architecture\, and operating systems. He has authored over 100 technical 
 papers and is best known for his work in Distributed Shared Memory (DSM) i
 n the context of the Clouds operating system\; and more recently for his w
 ork in stream-based distributed programming in the context of the Stampede
  system. Currently\, he is leading two inter-related projects\, ASAP/TC th
 at deals with camera sensor networks for situation awareness and Web on De
 mand that deals with system software stack for enabling transient social n
 etworking on mobile platforms. He has so far graduated 22 Ph.D. students w
 ho are well placed in academia and industries. He is currently advising 8 
 Ph.D. students. He is the recipient of an NSF PYI Award in 1990\, the Geor
 gia Tech doctoral thesis advisor award in 1993\, the College of Computing 
 Outstanding Senior Research Faculty award in 1996\, the College of Computi
 ng Dean's Award in 2003\, the College of Computing William ``Gus'' Baird T
 eaching Award in 2004\, and the 2009 “Freeman Award” for entrepreneurs
 hip in the College of Computing.\n
URL:https://www.tcs.tifr.res.in/web/events/251
DTSTART;TZID=Asia/Kolkata:20120220T113000
DTEND;TZID=Asia/Kolkata:20120220T123000
LOCATION:AG-80
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