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Dear SSA Canberra et al.,
Hope you are all keeping warm. Please see below for details on the next meeting, taking note of who to send RSVPs to for dinner.
Date: Tuesday 25 June
5.15pm Refreshments near lecture theatre 1, College of Business and Economics, ANU (Map).
6.00pm Presentation in lecture theatre 1
7.30pm After the talk, there will be a dinner at Delhi-6, Childers Street, Canberra (Restaurant).
Please RSVP Phil Tennant at Assistant Secretary or reply to this email directly by 24 June if you would like to attend the dinner.
Speaker: Matt Moores, University of Wollongong
Topic: Statistics from Mars: Bayesian signal processing for Raman spectroscopy
The planned Mars 2020 mission to Jezero crater will include a rover equipped with 2 Raman spectrometers: SuperCam and SHERLOC. This would be the first time that this type of spectroscopy has been performed on the Martian surface, which will enable new kinds of analysis of minerals and organic molecules. In the meantime, the Mars Science LaboratoryCuriosity rover continues to build on the massive dataset of laser-induced breakdown spectroscopy (LIBS) that it has been accumulating since 2012. These data pose particular challenges for statistical signal processing, since pre-flight calibration on Earth can only approximate Martian environmental conditions. Analytical methods must be robust to artefacts and other changes in the spectral profile, such as nonlinear interactions between signals. This talk will introduce a Bayesian method for source separation of spectroscopy. We derive informative priors from online databases of known reference spectra, as well as quantum-mechanical computer models. The components of the combined spectrum are identified and quantified using a sequential Monte Carlo algorithm. An open-source implementation of our method is available in the R package ‘serrsBayes.’
This is joint work with Kary Myers, Earl Lawrence & Sham Bhat (Los Alamos National Laboratory, USA), Jake Carson (University of Warwick, UK) and Mark Girolami (Alan Turing Institute for Data Science, UK).
Matt Moores is a lecturer in statistical science at the University of Wollongong. He is also a member of the National Institute for Applied Statistics Research Australia (NIASRA) and an Associate Investigator with ACEMS. Previously, Matt was a research fellow at the University of Warwick, UK, working on the EPSRC-funded projects i-like: “Intractable likelihood – new challenges from modern applications” and “in situ nanoparticle assemblies for healthcare diagnostics and therapy.” Matt completed his doctorate at QUT in 2015, under the supervision of Kerrie Mengersen & Fiona Harden. He also has extensive industry experience, having worked in R&D for international technology companies.
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