Rate My Professor Craig Butts

His research centers on organic molecular structure determination and reaction mechanisms, leveraging NMR spectroscopy. Key interests encompass experimental NMR method development, natural product structure elucidation, software tools for molecular structure analysis, computational modeling of solution-phase molecular dynamics, and machine learning for interpreting NMR data to predict three-dimensional structures. With over 130 research outputs and more than 8,000 citations, his contributions have profoundly influenced NMR-based structural chemistry. Landmark publications include 'Synergy of synthesis, computation and NMR reveals correct baulamycin structures' (Nature, 2017), 'Assembly-line synthesis of organic molecules with tailored shapes' (Nature, 2014), 'IMPRESSION – prediction of NMR parameters for 3-dimensional chemical structures using machine learning with near quantum chemical accuracy' (Chemical Science, 2020), 'Accuracy in determining interproton distances using Nuclear Overhauser Effect data from a flexible molecule' (Beilstein Journal of Organic Chemistry, 2011), and recent works such as 'Caylobolide B: Structure Revision, Total Synthesis, Biological Characterization, and Discovery of New Analogues' (Angewandte Chemie International Edition, 2025) and 'IMPRESSION generation 2 – accurate, fast and generalised neural network model for predicting NMR parameters' (Chemical Science, 2025). He leads projects like 'Modular Helical Foldamers To Drive A Rapid Asymmetric Catalyst Discovery Program' and secures funding for advanced NMR instrumentation, including a 700 MHz broadband cryoprobe.