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BSc PhD
Emma is a postdoctoral researcher in the Department of Physics, working at the intersection of chemistry and machine learning.
Emma began her career as an experimental chemist, performing undergraduate research with Professor Dean Toste at the University of California, Berkeley in organometallics methods development. Upon graduation, she joined the process chemistry team at Genentech (South San Francisco) for a year and gained a deep appreciation for total synthesis, prompting her return to academia for a PhD. Emma's graduate studies were completed under the tutelage of Professor Hans Renata at The Scripps Research Institute in Jupiter, Florida. During her tenure there, she gained expertise in enzyme-mediated total synthesis, developing novel routes to a wide range of molecules.
Currently, Emma is continuing her journey as a synthetic chemist, but this time with an emphasis in machine learning and is exploring the computational side of chemistry. Her postdoctoral research is supervised by Dr Alpha Lee and is centred around the investigation of how machine learning can be a tool for practical synthetic chemistry.
Emma's area of research is focused on providing practical solutions to synthetic chemistry challenges via the predictive power of machine learning. Specifically, Emma is interested in reaction outcome prediction: if given some molecules, how do they react? Although this type of prediction may be trivial for some workhorse reactions, prediction of many of the more complex reactions is challenging even for expert chemists. Machine learning, with its astonishing predictive power, is a potential solution to recognizing the subtle patterns that govern the seemly random outcomes of complex reactions.
Emma's research is funded by Pfizer (2021-2022) and a Newton International Fellowship (2022-2024).
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