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Research interests
Aiming to explore and accelerate the task of NMR structure elucidation through the implementation of machine learning with traditional computational methods.
Main areas of interest:
- AI & Machine learning
- Computational Chemistry
- High-throughput drug discovery
Publications
Recent publications
31/03/2025IMPRESSION generation 2
Chemical Science
IMPRESSION generation 2 - accurate, fast and generalised neural network model for predicting NMR parameters in place of DFT.
Chemical Science
Prediction of 15N chemical shifts by machine learning
Magnetic Resonance in Chemistry
Thesis
Machine Learning for Structure Elucidation in Pharmaceutical Applications
Supervisors
Award date
04/02/2025
