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We are very pleased to announce that Matt Moores from University of Wollongong will give a talk about Bayesian Analysis of Raman Spectroscopy at Sydney University in June.
Date: Thursday, 16th June 2022
Time: 6:30pm - 7:30pm (AEST)
Location: F10A.01.106.Law Building Annex.Law Annex Lecture Theatre 106 and on Zoom.
Attendence: Please RSVP here if attending in person to help us cater for the talk and make dinner reservations. Please register here if joining virtually for the Zoom link.
Matt Moores- University of Wollongong
Title: Bayesian Analysis of Raman Spectroscopy
Raman spectroscopy is a measurement technique that can be used to quantify the chemical composition of a sample. For example, the amount of alcohol in a glass of beer, or the presence of inflammatory biomarkers in blood. The “Perseverance” rover is currently using Raman spectroscopy to search for traces of ancient life on Mars. The main difficulties in analysing this data are due to multiple, overlapping peaks and a curved baseline. In this talk, I will describe a statistical model for joint estimation of the peaks and baseline. The locations of the peaks depend on the structure of the molecule, so it is often possible to obtain informative, Bayesian priors using computational chemistry. In the absence of such prior information, we can model the peak locations as a point process. We fit this model using a sequential Monte Carlo (SMC) algorithm, which we have implemented in the R package “serrsBayes.”
This is joint work with Lassi Roininen, Teemu Härkönen, Emma Hannula & Erik Vartiainen (LUT, Finland), Jake Carson (Warwick, UK), Mark Girolami (Cambridge, UK), Kirsten Gracie, Karen Faulds & Duncan Graham (Strathclyde, UK).
Härkönen, Hannula, Moores, Vartiainen & Roininen (2022). “A log-Gaussian Cox process with sequential Monte Carlo for line narrowing in spectroscopy.” https://doi.org/10.48550/arXiv.2202.13120
Moores, Carson, Moskowitz, Gracie, Faulds & Girolami (2021) “R package serrsBayes” version 0.4-2 https://doi.org/10.5281/zenodo.3861862
Härkönen, Roininen, Moores & Vartiainen (2020). “Bayesian quantification for coherent Anti-Stokes Raman scattering spectroscopy.” The Journal of Physical Chemistry B, 124(32), 7005-7012. https://doi.org/10.1021/acs.jpcb.0c04378
Moores, Gracie, Carson, Faulds, Graham & Girolami (2016). “Bayesian modelling and quantification of Raman spectroscopy.” https://doi.org/10.48550/arXiv.1604.07299
Matt completed his doctorate at QUT in 2015, under the supervision of Kerrie Mengersen and Fiona Harden. He was then appointed as a postdoctoral research fellow in the Department of Statistics at the University of Warwick, UK, first under the supervision of Mark Girolami, before joining the “i-Like” project under the supervision of David Firth. He joined the University of Wollongong in 2018 with a continuing lectureship in statistical science. In 2021, he was awarded the title of Docent in Computational Statistics at Lappeenranta University of Technology (LUT), Finland. Matt’s research interests include MCMC and SMC algorithms for intractable likelihoods and inverse problems in spectroscopy, satellite remote sensing, and data-centric engineering.
This is an in person event event, and we hope you can join us at Sydney Uni. If you would like to attend virtually, the Zoom registration link is https://uni-sydney.zoom.us/meeting/register/tZcrdO6rrj4oHNA3e9VLOoyHw99kTZsHKiH7. Please note for security reasons, you will need to register in advance for this meeting. After registering, you will receive a confirmation email containing information about joining the meeting.
Any questions, please feel free to contact: firstname.lastname@example.org
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