Max Hart
My project, supervised by Dr. Gabriel Facini, will focus on using novel machine learning techniques to improve track reconstruction at the ATLAS experiment at the LHC.
![Max](/data-intensive-science-industry/sites/data_intensive_science_industry/files/max-feed.jpg)
1 January 2022
Project title:ÌýExploring the possible applications of quantum algorithms to the data produced by experiments at the LHC
Research Group:
³§³Ü±è±ð°ù±¹¾±²õ´Ç°ù(²õ):ÌýDr Gabriel Facini
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I obtained my BSc in Theoretical Physics from Imperial College London, where I did summer research placements working on plasma pedestal simulation in MAST at CCFE, and background identification at CMS at the LHC in my second and third years respectively. After graduating, I worked as a data scientist at a small prop-tech startup for a year before completing an MSc in Statistics, also at Imperial. The CDT in DIS appeals to me as it provides the opportunity to pursue research in fundamental physics like in a traditional PhD track, whilst also giving the opportunity to use the skills obtained from this research in industry. My project, supervised by Dr. Gabriel Facini, will focus on using novel machine learning techniques to improve track reconstruction at the ATLAS experiment at the LHC.Ìý
Project description:ÌýÌý
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First year group project:Ìý
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