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SUMMARY:Interpreting (chemical) forensic evidence in a Bayesian framework:
  a multidisciplinary task - Gabriel Vivó-Truyols (Universiteit van Amster
 dam)
DTSTART:20161108T093000Z
DTEND:20161108T101500Z
UID:TALK68867@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:<span>         Co-authors: Marjan Sjerps 		(University of Amst
 erdam / Dutch Forensic Institute)\, Martin Lopatka 		(University of Amster
 dam / Dutch Forensic institute)\, Michael Woldegebriel 		(University of Am
 sterdam)\, Andrei Barcaru 		(University of Amsterdam)        <br></span><s
 pan>&nbsp\;<br>The interpretation and evaluation of chemical forensic evid
 ence is a  challenging task of multidisciplinary nature. Interaction betwe
 en  diferent disciplines (Bayesian statisticians\, analytical chemists\,  
 signal processers\, instrument expers\, etc.) is necessary.  In this talk 
 I will illustrate different cases of such interaction to  evaluate pieces 
 of evidence in a forensic context:  The first case is the evaluation of fi
 re debris using two-dimensional  gas chromatography. Such a technique anal
 yses fire debris to look for  traces of (pyrolized) hydrocarbons. However\
 , the classification of such  hydrocarbons is a difficult task\, demanding
  experts in (analytical)  chemistry. Even more difficult is to interpret s
 uch evidence in a  Bayesian framework.  The second case is the application
  of Bayesian inference in the  toxicology laboratory. In this case\, a set
  of targeted compounds is  analysed via LC-MS. Instruments are normally pr
 e-processing the data in a  deterministic manner\, providing the so-called
  peak table. We propose an  alternative that uses the raw data as evidence
 \, instead of using such  peak table.  The third case is the exploration o
 f differences between different  analysis\, in order to find illegal addit
 ives in a complex matrix. In  this case\, the use of Jensen-Shannon diverg
 ence has been applied in a  Bayesian framework to highlight such differenc
 es.</span>
LOCATION:Seminar Room 1\, Newton Institute
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