Using Deep Learning to Transform and Analyse NMR Data
During the 55th session of the Global NMR Discussion Meetings held on November 1st, 2022 via Zoom, Prof. Flemming Hansen from University College London, gave a talk on the topic "Using Deep Learning to Transform and Analyse NMR Data". The recording serves as a tutorial.
It will be shown how deep neural networks (DNNs) can be trained for reconstruction of sparsely sampled NMR spectra and for virtual homonuclear decoupling. Another area covered in the talk will be autonomous analysis of chemical exchange saturation transfer (CEST) data, where the trained DNN accurately predicts both the chemical shifts and the uncertainties associated with these.
Speaker's biography:
1997-2003: BSc+MSc, Chemistry + Physics, University of Copenhagen
2003-2005: PhD in Biophysical Chemistry (Prof. Jens Led) , University of Copenhagen
2005-2010: Postdoctoral fellow (Prof Lewis E. Kay), University of Toronto
2010-present: PI, University College London. Full Professor since 2017.
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Twitter: https://twitter.com/dflemminghansen?l...
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Website: https://www.ucl.ac.uk/hansen-lab/flem...