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UID:www.tcs.tifr.res.in/event/556
DTSTAMP:20230914T125929Z
SUMMARY:Mobile Sensing: Efficient Sampling and Privacy Concerns
DESCRIPTION:Speaker: Jayakrishnan Unnikrishnan (Ecole Polytechnique Federal
 e de Lausanne\nSchool of Computer and Communication Sciences\nEPFL-IC-LCAV
 \nStation 14\nCH-1015 Lausanne\nSwitzerland)\n\nAbstract: \nAbstract: Sens
 ing of spatial fields is traditionally studied in a setting where static s
 ensors take measurements of the spatial field at their locations. However 
 many modern applications like citizen sensing and robotic sensing employ m
 oving sensors for spatial sensing. This emerging paradigm of mobile sensin
 g requires us to rethink the classical notions of sampling and privacy. In
  this talk I will focus on the following aspects.\n(1) A sampling theory f
 or mobile sensing: We introduce the notion of path density\, defined as th
 e total distance traveled by the mobile sensors per unit spatial volume. W
 e design sensor trajectories that are efficient in terms of path density f
 or sampling spatially bandlimited fields\, and obtain fundamental limits o
 n the path density of mobile sensor trajectories that admit stable samplin
 g. These limits are analogous to Landau-Nyquist rates for classical sampli
 ng (joint work with M. Vetterli\, J.L. Romero\, K. Grochenig).\n(2) Privac
 y of mobility statistics: How private are anonymized mobility statistics? 
 We study the de-anonymization of anonymized mobility statistics as a hypot
 hesis testing problem\, and identify the optimal scheme for matching anony
 mized location histograms to auxiliary observations of the users' location
 s. We apply the scheme to datasets of Wi-Fi traces\, call data records\, a
 nd web browsing histories to highlight the privacy concerns in collecting 
 location information in citizen sensing schemes (joint work with F. Naini\
 , P. Thiran\, M. Vetterli).\nIn sum\, citizen sensing opens up possibiliti
 es for efficient spatial sampling at the risk of raising privacy issues. I
  will quantify both aspects in this talk and present new algorithms and de
 monstrate their usefulness by applying them on real data.\nBio: Jayakrishn
 an Unnikrishnan received the B.Tech. degree in electrical engineering from
  the Indian Institute of Technology\, Madras in 2005 and the M.S. and Ph.D
 . degrees in electrical and computer engineering from the University of Il
 linois at Urbana-Champaign in 2007 and 2010\, respectively.\nFrom 2010 to 
 2014\, he worked as a postdoctoral researcher at the School of Computer an
 d Communication Sciences\, Ecole Polytechnique Federale de Lausanne (EPFL)
 \, Lausanne\, Switzerland. His current research interests include signal p
 rocessing\, detection and estimation theory\, and information theory.\nDr.
  Unnikrishnan is a recipient of the Vodafone Graduate Fellowship Award fro
 m the University of Illinois at Urbana-Champaign for 2007--2008 and the E.
 A. Reid Fellowship Award from the ECE department at the University of Illi
 nois at Urbana-Champaign for 2010--2011.\n
URL:https://www.tcs.tifr.res.in/web/events/556
DTSTART;TZID=Asia/Kolkata:20141215T103000
DTEND;TZID=Asia/Kolkata:20141215T120000
LOCATION:D-405 (D-Block Seminar Room)
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