Emma King-Smith

Dr Emma King-Smith is a researcher in the School of Chemistry at The University of Edinburgh. Her work focuses on synthetic organic chemistry, reaction prediction, machine learning, and artificial intelligence. She explores how molecular reactivity influences reaction yields and interactions with the human body, using deep learning and AI to develop predictive models. Her research emphasizes experimental validation to enhance understanding of small organic compounds' reactivity. Dr King-Smith's work includes studies on direct-to-biology workflows, transfer learning for foundational chemistry models, and predictive Minisci late-stage functionalization. She also investigates the chemical 'reactome' through high-throughput experimentation.

Emma King-Smith is a Chancellor's Fellow at the University of Edinburgh, specializing in Organic Chemistry and Machine Learning. Her research focuses on the synthesis of complex natural products using advanced methodologies such as chemoenzymatic and radical-based retrosynthetic strategies. She integrates machine learning to enhance chemical reaction prediction and optimize synthetic pathways. Her work includes the development of predictive models for late-stage functionalization and crystallographic chiral separation. By merging organic synthesis with computational tools, she aims to improve the efficiency and scalability of chemical processes. Her research bridges the gap between experimental chemistry and data-driven approaches, contributing to the fields of medicinal chemistry and sustainable synthesis.