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SUMMARY:Bayesian intelligent structural health monitoring - Dr Sn-Chi Kuok
 \, Academic Visitor\, Department of Engineering Science at University of O
 xford
DTSTART:20190614T140000Z
DTEND:20190614T150000Z
UID:TALK125920@talks.cam.ac.uk
CONTACT:Karen Mitchell
DESCRIPTION:Bayesian intelligent structural health monitoring (BISHM) inte
 grates Bayesian inference and machine learning to develop an effective and
  efficient framework for reliable structural health monitoring (SHM). Baye
 sian inference provides a rigorous scheme for utilizing the available info
 rmation to determine the optimal estimates and quantify the associated est
 imation uncertainty in the form of probability distribution. On the other 
 hand\, machine learning offers a powerful computational environment to aut
 omate analytical modeling and handle tremendous amount of dynamic data str
 eams. By exploiting the remarkable features of Bayesian inference and mach
 ine learning\, BISHM offers a promising direction to tackle challenging is
 sues encountered in SHM investigation. In this seminar\, our recent develo
 pments on BISHM and the applications to benchmark SHM projects will be pre
 sented. \n\nBiography: \nDr. Kuok is an academic visitor in the Department
  of Engineering Science at University of Oxford. She received her Ph.D. de
 gree in Civil Engineering from University of Macau in 2015 and worked as a
  postdoctoral scientist at Cornell University afterward. Since 2018\, she 
 has been being employed as a lecturer at University of Macau and she is cu
 rrently under a two-years collaborative research program in UK. Her resear
 ch interest focuses on developing reliable structural health monitoring me
 thodologies via Bayesian inference and machine learning. The implementatio
 ns of her developed algorithms cover model class selection\, optimal senso
 r network configuration design\, signal pre-processing\, outlier cleansing
 \, system identification\, seismic attenuation modeling\, structural healt
 h indicator interpretation\, and wind-structural interaction analysis.\n
LOCATION: Cambridge University Engineering Department\, LT6
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