I am a member of the BAS AI lab working on the development of a Digital Twin of the RRS Sir David Attenborough (SDA). This project aims to integrate a diverse range of sensor measurements and remote sensing information with route planning and scheduling algorithms in order to provide automated decision support to the SDA crew. These efforts will focus on delivering optimal fuel economy and minimising carbon emissions as part of BAS’s commitment to achieve Net Zero carbon emissions by 2040. My current focus is on the implementation of ice features within the digital twin model including ice resistance forces, leads, polynyas and icebergs.
In a previous life I completed a PhD in experimental particle physics at the University of Glasgow as a member of the LHCb experiment at CERN. This work focused on making measurements of the structure of the LHC beams using a gas target and LHCb’s high precision vertex locator. I subsequently spent two years working as a machine learning engineer in the field of natural language processing.
G. Coombs, Beam-Gas Imaging at the LHCb Experiment, PhD Thesis, University of Glasgow, CERN-THESIS-2021-058, https://cds.cern.ch/record/2767576
G. Coombs et al., Beam-Gas Imaging Measurements at LHCb, Proceedings of IBIC2018, Shanghai, China, 2018, doi:10.18429/JACoW-IBIC2018-WEPB13
R. Alemany-Fernandez et al., Cross-Calibration of the LHC Transverse Beam-Profile Monitors, Proceedings of IPAC2017, Copenhagen, Denmark, MOPAB130
T. Hadavizadeh et al., Transverse Emittance Measurements Using LHCb’s Beam-Gas Interactions, Proceedings of IPAC2017, Copenhagen, Denmark, MOPAB131
X. Buffat et al., Beam-beam Effects in Different Luminosity Levelling Scenarios for the LHC, Proceedings of IPAC2014, Dresden, Germany, doi:10.18429/JACoW-IPAC2014-TUPRO023
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