Vaibhav Kumar Shukla

This paper uses deep neural networks to reconstruct 2D NMR spectra from single-pulse experiments, eliminating transfer delays and enabling high-quality methyl correlation maps for large proteins.

This paper develops a deep neural network, FID-Net-2, combined with custom NMR experiments to accurately reconstruct high-resolution aromatic 1H-13C correlation spectra from uniformly 13C-labeled protein samples.

This paper uses MD simulations, NMR, and SAXS to characterise the cis and trans proline conformations of ORF6CTR from SARS-CoV-2, showing good agreement between simulations and experiments.