Digital Twins of the Polar Regions
This project is developing digital twins of Antarctic and Arctic environments and resources. A digital twin makes it possible to test “what if” questions far more quickly than traditional computer models.
I am a member of the BAS AI lab working within the Autonomous Marine Operations Planning (AMOP) group. This project is focused on developing a suite of Artificial Intelligence (AI) methods that aim to optimise the efficiency of Antarctic field operations, while maximising science delivery. This will help to deliver part of BAS’s commitment to achieve Net Zero carbon emissions by 2040.
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
Co-author:
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
This project is developing digital twins of Antarctic and Arctic environments and resources. A digital twin makes it possible to test “what if” questions far more quickly than traditional computer models.
AMOP is developing Artificial Intelligence methods that aim to optimise the efficiency of Antarctic field operations, while maximising science delivery
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